INTERNATIONAL 

FOOD AID

Prepositioning 

Speeds Delivery of 

Emergency Aid, but 

Additional Monitoring 

of Time Frames and 

Costs Is Needed

Report to the Chairwoman, Committee 

on Agriculture, Nutrition, and Forestry, 

U.S. Senate

March 2014

GAO-14-277

United States Government Accountability Office
United States Government Accountability Office

Highlights of GAO-14-277, a report to the 

Chairwoman, Committee on Agriculture, 

Nutrition, and Forestry, U.S. Senate

March 2014

INTERNATIONAL FOOD AID

Prepositioning Speeds Delivery of Emergency Aid, but Additional Monitoring of Time Frames and Costs 

Is Needed

Why GAO Did This Study

Through Title II of the Food for Peace 

Act, the United States provides U.S. 

agricultural commodities to meet 

emergency food needs in foreign 

countries. In fiscal years 2007 to 2012, 

USAID delivered $9.2 billion in

emergency food aid to recipient

countries through cooperating 

sponsors. In 2000, Congress 

authorized USAID to order, transport, 

and store food for prepositioning in 

both overseas and domestic locations. 

Through prepositioning, the agency

orders food before it is requested and 

stores it in warehouses in or near 

regions with historically high needs.

GAO was asked to examine U.S. 

international food aid procurement. 

This report examines (1) the effects of 

prepositioning on emergency food aid 

delivery time frames, (2) the effects of 

prepositioning on the costs of the food 

aid, and (3) the extent to which the 

agency monitors prepositioning to 

maximize time savings and cost 

effectiveness. GAO analyzed data on 

delivery time frames and costs; 

reviewed agency documents; and 

interviewed agency officials and

representatives from WFP, other 

cooperating sponsors, and ocean 

freight contractors. 

What GAO Recommends

GAO recommends that USAID 

systematically collect, and ensure the 

reliability of, data for prepositioned 

food aid and systematically monitor 

and assess the effectiveness of food 

aid’s delivery time frames and costs. 

USAID concurred with the 

recommendations and is working to 

improve both the collection of reliable 

data and its monitoring of 

prepositioning. 

What GAO Found

The U.S. Agency for International Development (USAID) reduces the average 

delivery time frame for emergency food aid by prepositioning food domestically—

that is, in warehouses in the United States—and overseas. GAO estimates that 

compared with USAID’s standard shipping process, which can take several 

months, prepositioning food aid shortened delivery time frames by an average of 

almost a month for shipments to the World Food Program (WFP). GAO also 

estimates that prepositioning shortened delivery time frames by an average of

more than 2 months for other organizations—“cooperating sponsors”—that 

receive USAID grants. In addition, USAID reduces delivery time frames when it 

diverts shipments en route to overseas prepositioning warehouses to areas with 

immediate needs. For all cooperating sponsors, GAO estimates that diversions 

saved, on average, about 2 months. 

Illustration of Time Savings from USAID Prepositioning of Emergency Food Aid

Prepositioning food can increase the cost of emergency food aid because of 

additional warehouse, shipping, and commodity costs. For example, in fiscal year 

2012, USAID paid approximately $8 million for its overseas and domestic 

prepositioning warehouses. USAID also paid $13 million to ship food by ocean 

freight from overseas prepositioning warehouses to recipient countries, in

addition to the cost of shipping from the United States to the warehouses. 

Further, USAID generally paid higher weighted annual average prices for 

domestically prepositioned commodities than for standard shipment 

commodities. U.S. officials and vendors noted that factors such as limited

commodity supplies and few participating suppliers may have contributed to 

higher prices. 

USAID has taken some steps to evaluate prepositioning, but the agency does not

collect and analyze data needed to systematically monitor delivery time frames 

for prepositioned commodities. In addition, some available data are unreliable. 

Further, USAID does not systematically monitor the total cost of prepositioning. 

According to USAID policy and federal internal control standards, the agency 

should monitor its programs by collecting and analyzing data to guide higherlevel decision making and allocate resources. Without such monitoring, USAID is

limited in its ability to assess prepositioning’s impact on delivery time frames and 

View GAO-14-277. For more information, costs and to maximize emergency food aid’s timeliness and cost effectiveness.

contact Thomas Melito at (202) 512-9601 or 

MelitoT@gao.gov.
Page i GAO-14-277 Prepositioning of Emergency Food Aid

Letter 1 

Background 3

USAID’s Prepositioning of Emergency Food Aid Shortens Delivery 

Time Frames 7

Prepositioning Emergency Food Aid Involves Additional Costs 12

USAID Does Not Systematically Monitor Prepositioning to 

Maximize Time Savings and Cost Effectiveness 17

Conclusions 21

Recommendations for Executive Action 22

Agency Comments 22

Appendix I Objectives, Scope, and Methodology 24

Appendix II Delivery Time Frames Regression Analysis 29

Appendix III Examples of Additional Ocean Shipping Costs for Overseas 

Prepositioning 46

Appendix IV Analysis of Weighted Annual Average Prices for Domestic and 

Overseas Prepositioned Commodities 47

Appendix V Related GAO Products about International Food Aid 50

Appendix VI Comments from the U.S. Agency for International Development 52

Appendix VII GAO Contact and Staff Acknowledgments 54

Contents
Page ii GAO-14-277 Prepositioning of Emergency Food Aid

Tables

Table 1: Estimated Days Saved by USAID’s Prepositioning of 

Emergency Food Aid for the World Food Program, 

Compared with Standard Shipping, Fiscal Years 2009- 

2012 8

Table 2: Estimated Days Saved by USAID’s Prepositioning of 

Emergency Food Aid for Nine Cooperating Sponsors, 

Compared with Standard Shipping, Fiscal Years 2007-

2012 9

Table 3: Estimated Days Saved by USAID’s Diversion of 

Prepositioning of Emergency Food Aid Shipments, 

Compared with Standard Shipping, Fiscal Years 2007–

2012 11

Table 4: Annual Targets and Total Expenditures for USAID 

Overseas Prepositioning Warehouses, Fiscal Years 2011 

and 2012 14

Table 5: Percentages and Costs of Ocean Shipping of Emergency 

Food Aid from Overseas Prepositioning Warehouses, 

Fiscal Year 2012 15

Table 6: Numbers of Emergency Food Aid Shipments 

Represented in Data Included in GAO Analysis 30

Table 7: Numbers of Emergency Food Aid Shipments 

Represented in Data Excluded from GAO Analysis and 

the Reasons for Exclusion 31

Table 8: Average Delivery Time Frames (in Days) for Emergency 

Food Aid Shipments 34

Table 9: Estimated Days Saved by USAID’s Prepositioning 

Emergency Food Aid for the World Food Program, 

Relative to Standard Shipping, Fiscal Years 2009- 2012 35

Table 10: Estimated Days Saved by USAID’s Prepositioning 

Emergency Food Aid for Nine Cooperating Sponsors, 

Relative to Standard Shipping, Fiscal Years 2007-2012 38

Table 11: Estimated Days Saved by USAID’s Diversion of 

Prepositioning Emergency Food Aid Shipments, Relative 

to Standard Shipping, Fiscal Years 2007–2012 42

Table 12: Illustrative Examples of Additional Costs for Ocean 

Shipping from Djibouti in Fiscal Year 2012, per Metric Ton 46

Table 13: Numbers of Domestic Prepositioning and Standard 

Shipment Purchases for Six Key Commodities, Fiscal 

Years 2007-2012 49
Page iii GAO-14-277 Prepositioning of Emergency Food Aid

Figures

Figure 1: USAID Processes for Delivering Emergency Food Aid 5

Figure 2: Percentage Differences between Weighted Annual 

Average Prices That USAID Paid for Six Domestically 

Prepositioned Commodities and Standard Shipment 

Commodities, Fiscal Years 2007-2012 16

Figure 3: Percentage Differences between Weighted Annual 

Average Prices for USAID’s Domestically and Overseas 

Prepositioned Commodities Relative to StandardShipment Commodities, Fiscal Years 2007-2012 48

Abbreviations

Title II Title II of the Food for Peace Act 

UNICEF United Nations Children’s Fund

USAID U.S. Agency for International Development

USDA U.S. Department of Agriculture

WFP United Nations World Food Program

This is a work of the U.S. government and is not subject to copyright protection in the 

United States. The published product may be reproduced and distributed in its entirety 

without further permission from GAO. However, because this work may contain 

copyrighted images or other material, permission from the copyright holder may be 

necessary if you wish to reproduce this material separately.
Page 1 GAO-14-277 Prepositioning of Emergency Food Aid

441 G St. N.W.

Washington, DC 20548

March 5, 2014

The Honorable Debbie Stabenow

Chairwoman

Committee on Agriculture, Nutrition, and Forestry

United States Senate

Dear Madam Chairwoman:

U.S. international emergency food aid assists nations affected by severe 

ongoing crises, such as the long-term food shortage in Ethiopia, as well 

as unanticipated crises, such as the 2010 earthquake in Haiti. In fiscal 

years 2007 to 2012, the United States donated about $9.2 billion in 

emergency food aid to recipient countries under Title II of the Food for 

Peace Act (Title II).1 The U.S. Agency for International Development’s 

(USAID) Office of Food for Peace, which is responsible for managing the 

U.S. emergency food aid program, delivers this assistance through 

cooperating sponsors such as the World Food Program (WFP), Catholic 

Relief Services, and Save the Children.2 In 2005, to expedite the delivery 

of emergency food aid, USAID began to stockpile, or preposition, food 

commodities, such as lentils, peas, and vegetable oil, in or near regions 

of the world with historically high emergency food needs. From 2007 to 

2012, USAID increased the tonnage of commodities that it ordered for 

prepositioning under Title II from 6 percent to 22 percent of all emergency 

food aid commodities. To address immediate needs, USAID can also 

redirect, or divert, commodities intended for prepositioning and ship them 

directly to areas in crisis.

In 2000, Congress authorized USAID to order, transport, and store food 

for prepositioning in the United States and in foreign countries.3 Since 

 

1

See 7 U.S.C. § 1721 et seq. Section 3001 of Pub L. No. 110-246, the Food, 

Conservation, and Energy Act of 2008, renamed the underlying legislation, the Agricultural 

Trade Development Aid Act of 1954 (also known as P.L. 480), as the Food for Peace Act.

2

Cooperating sponsors are organizations that have received USAID grants for delivery of 

emergency food aid to recipient countries. Shipments of cooperating sponsors’ emergency 

food aid are tracked by freight forwarders—contractors that manage the supply chain of 

these shipments.

3

Pub. L. No. 106-472, §310(b). 
 

Page 2 GAO-14-277 Prepositioning of Emergency Food Aid

2008, Congress has authorized up to $10 million annually for storage of 

food in overseas prepositioning sites.4 The Farm Bill signed by the 

President in February 2014 increased the authorization for overseas 

prepositioning storage costs to $15 million annually.5 For this report, you 

asked us to assess several issues related to U.S. international food aid 

procurement. This report examines the (1) effects of USAID’s 

prepositioning on delivery time frames for emergency food aid 

shipments,6 (2) the effects of prepositioning on the costs of emergency 

food aid, and (3) the extent to which the agency monitors prepositioning 

to maximize time savings and cost effectiveness.

To determine the effects of USAID’s prepositioning on the delivery time 

frames and costs of emergency food aid, we analyzed data for 3,785 

emergency food aid shipments in fiscal years 2007 through 2012.7 We 

used characteristics such as commodity type, month and year the 

commodity was requested, and discharge port to control for the 

differences between standard and prepositioned emergency food aid 

shipments. We conducted separate analyses, and present separate 

findings, on the effects of prepositioning for WFP and the other 

cooperating sponsors because of differences in time periods and 

shipment dates tracked.8 We also analyzed cost data related to 

emergency food shipments in fiscal years 2007 through 2012. To 

determine the extent to which USAID has monitored prepositioning, we 

reviewed agency documents to assess whether USAID’s monitoring was 

consistent with its policy and regulations. We interviewed officials of U.S. 

agencies, WFP and one other cooperating sponsor, and freight 

 

4

The Food Conservation and Energy Act of 2008, Pub. L. No. 110-246, increased the 

authorized level of funding for overseas storage from $2 million to $10 million

5

Pub. L. No. 113-79, §3009.

6

We calculated delivery time frames as the number of days between a cooperating 

sponsor’s request for emergency food aid commodities and the commodities’ arrival at the 

discharge port or in the recipient country. We chose the request for food as the starting 

point for delivery time frames because the goal of prepositioning is to expedite the delivery 

of requested emergency food aid.

7

We collected data for 5,142 emergency food aid shipments and analyzed data for 3,785 

(74 percent) of these shipments. Our analysis excludes data for the remaining shipments 

because of a number of data limitations (see app. II). Our estimates are not representative 

of the shipments not included in our analysis.

8

See appendix II for full description of our methodology and results. 
 

Page 3 GAO-14-277 Prepositioning of Emergency Food Aid

forwarders—contractors that manage the supply chain of emergency food 

aid for USAID and its cooperating sponsors—in Washington, D.C. 

Appendixes I though IV contain additional information on our scope and 

methodology.

We conducted this performance audit from July 2013 to March 2014 in 

accordance with generally accepted government auditing standards. 

Those standards require that we plan and perform the audit to obtain 

sufficient, appropriate evidence to provide a reasonable basis for our 

findings and conclusions based on our audit objectives. We believe the 

evidence obtained provides a reasonable basis for our findings and 

conclusions based on our audit objectives.

To respond to food aid emergencies, USAID can provide emergency food 

aid commodities through four general delivery processes: standard 

shipping, overseas prepositioning, domestic prepositioning, or diversion 

(see fig. 1).9 USAID determines the most appropriate of these four 

processes by analyzing the request for food aid, the nature of the 

emergency, and the availability of commodities and resources. USAID 

aims to maintain a combined total of up to 100,000 metric tons of food in 

its prepositioning supply chain at any given time.10 USAID currently 

maintains prepositioning warehouses in six overseas locations (Colombo, 

Sri Lanka; Djibouti, Djibouti; Dubai, United Arab Emirates; Durban, South 

 

9

In the food aid community, “diversion” generally refers to loss or theft of food aid. 

However, USAID and cooperating sponsors also use “diversion” to refer to the redirection 

of food aid from some stage of the prepositioning process to a foreign port to meet 

immediate needs. In this report, “diversion” has the latter meaning. 

10According to USAID, the agency varies the inventory of each warehouse throughout the 

year to align prepositioned food aid with anticipated program needs, availability of funding, 

and warehouse space. 

Background
 

Page 4 GAO-14-277 Prepositioning of Emergency Food Aid

Africa; Las Palmas, Spain; and Mombasa, Kenya) and two domestic 

locations (Jacinto Port, Texas, and Miami, Florida).11

 

11Two of USAID’s current prepositioning warehouses—in Dubai, United Arab Emirates, 

and Miami, Florida—were opened in 2013. According to USAID, these two warehouses 

are used only to preposition specialized emergency food products and are managed 

separately from USAID’s other prepositioning warehouses. Since the scope of our review 

is 2007 through 2012, we did not include the Dubai and Miami warehouses in our 

analysis. Before 2013, USAID also operated prepositioning warehouses in Lake Charles, 

Louisiana, and Lomé, Togo, but the agency no longer uses these warehouses for 

prepositioning. Because data were available for the Lomé warehouse, we included these 

data in our analysis. Data were not available for the Lake Charles warehouse, which 

closed in 2007. Jacinto Port is located in Houston, Texas.
 

Page 5 GAO-14-277 Prepositioning of Emergency Food Aid

Figure 1: USAID Processes for Delivering Emergency Food Aid
 

Page 6 GAO-14-277 Prepositioning of Emergency Food Aid

Notes: The descriptions shown for each stage of the process are illustrative examples and do not 

reflect all emergency food aid shipments. For instance, diversions can occur at any point in the 

procurement, transportation, and shipping process.

USAID’s two domestic warehouses are in Jacinto Port, Texas, and Miami, Florida.

USAID’s six overseas warehouses are in Colombo, Sri Lanka; Dubai, United Arab Emirates; Durban, 

South Africa; Djibouti, Djibouti; Las Palmas (Canary Islands), Spain; and Mombasa, Kenya. Before 

2013, USAID also had prepositioning warehouses in Lake Charles, Louisiana, and Lomé, Togo; the 

agency stopped using these warehouses for prepositioning in 2007 and 2012, respectively.

In 2007, we reported that U.S. food aid delivery is generally too time 

consuming to be sufficiently responsive in emergencies, requiring 4 to 6 

months on average, including time required for procurement and 

transportation of the commodities.12 We recommended, among other 

things, that USAID conduct a cost-benefit analysis of prepositioning to 

improve its food aid logistical planning. In 2008, USAID commissioned a 

cost-benefit analysis of the U.S. government’s food prepositioning 

activities. The commissioned analysis did not compare the timeliness of 

domestic and overseas prepositioning; however, it recommended that 

USAID consider increasing the amount of food aid prepositioned 

domestically, to improve its response times to critical emergency program 

needs.13 In 2013, a report by USAID’s Inspector General found that the 

agency had not determined whether the benefits of overseas 

prepositioning in the Horn of Africa outweighed the costs or whether 

overseas prepositioning saved time in comparison with domestic 

prepositioning.14

 

12GAO, Foreign Assistance: Various Challenges Impede the Efficiency and Effectiveness 

of U.S. Food Aid, GAO-07-560 (Washington, D.C.: Apr. 13, 2007).

13Janet R. van der Vaart, P.L. 480 Title II Pre-positioning Cost/Benefit Analysis (2008).

14U.S. Agency for International Development, Office of Inspector General, Audit of 

USAID’s Internal Controls Over Prepositioned Food Assistance for the Horn of Africa, 

Audit Report No. 4-962-13-004-P (Jan. 7, 2013). 
 

Page 7 GAO-14-277 Prepositioning of Emergency Food Aid

Prepositioning of emergency food aid reduces the average delivery time 

frame for USAID’s food aid shipments for WFP and other cooperating 

sponsors.15 For WFP, prepositioning food aid in overseas and domestic 

warehouses shortened delivery time frames by an average of almost a 

month. For nine of USAID’s other cooperating sponsors, prepositioning 

food aid in domestic and overseas warehouses shortened delivery time 

frames by an average of more than 2 months.16 In addition, diversion of 

emergency food aid from the prepositioning process shortened delivery 

time frames by, on average, about 2 months for WFP and the other 

sponsors.17

We estimated, using statistical modeling to control for various factors, that 

prepositioning food in overseas and domestic warehouses shortened the 

average delivery time frame for shipments for WFP by 28 days in fiscal 

years 2009 through 2012 compared with USAID’s standard shipping 

process. As table 1 shows, during this period, the 472 prepositioned 

shipments for WFP had an average delivery time frame of about 102 

days. In contrast, the 1,665 standard shipments for WFP had an average 

delivery time frame of 135 days.18 According to WFP officials, USAID’s 

 

15We conducted analyses, and discuss our findings, of delivery time frames for USAID 

food aid shipments for WFP and nine other cooperating sponsors separately because the 

two groups of data differ in the time periods covered and in their treatment of food aid 

diversions.

16The nine cooperating sponsors are CARE, Catholic Relief Services, the government of 

Pakistan, Norwegian People’s Aid, Relief Society of Tigray, SHARE Guatemala, Save the 

Children, Save the Children—United Kingdom, and the United Nations Children’s Fund 

(UNICEF). Shipment data for these nine cooperating sponsors are collected and tracked 

by three freight forwarders. We collected shipment data for additional cooperating 

sponsors from three other freight forwarders; however, we did not find these data to be 

sufficiently reliable for our purposes and did not include them in our analysis. See 

appendixes I and II for a detailed discussion of our methodology and results.

17Our estimate of delivery time frames of diverted shipments for WFP and other 

cooperating sponsors uses data obtained primarily from a single freight forwarder. These 

data do not display the differences we identified between the data for WFP and the data 

for the other cooperating sponsors. We found these data to be reliable for estimating the 

effect of emergency food aid diversions on delivery time frames for both WFP and the 

other sponsors. See appendixes I and II for a detailed discussion of our methodology and 

results. 

18We used regression analysis to estimate the number of days saved, controlling for 

various factors such as commodity type and discharge port. As a result, the numbers of 

days saved does not equal the difference between the average delivery time frames.

USAID’s 

Prepositioning of 

Emergency Food Aid 

Shortens Delivery

Time Frames

For WFP, Prepositioning 

Emergency Food Aid 

Shortened Average 

Delivery Time Frame by 

Almost a Month
 

Page 8 GAO-14-277 Prepositioning of Emergency Food Aid

prepositioning of food in warehouses has helped WFP provide food aid 

more quickly. WFP officials also stated that because prepositioned food is 

available for immediate collection from warehouses, prepositioning helps 

ensure a sufficient food aid supply to meet spikes in demands due to 

unforeseen emergencies.

19

Table 1: Estimated Days Saved by USAID’s Prepositioning of Emergency Food Aid for the World Food Program, Compared 

with Standard Shipping, Fiscal Years 2009- 2012

 

Number of days saved 

(regression results)

Margin of error at

95 percent confidence (days)

Average delivery

time frame (days)

Number

of shipments

Standard shipping - - 135 1,665

All prepositioning 28a 15 102 472

Overseas prepositioning 41a 17 92 262

Domestic prepositioning 16b 17 114 210

Source: GAO analysis of World Food Program (WFP) data.

Notes:

For all prepositioning, overseas prepositioning, and domestic prepositioning, we used regression 

analysis to estimate the number of days saved, controlling for various factors such as commodity type 

and discharge port. As a result, the numbers of days saved do not equal the differences between 

average delivery time frames. For example, the number of days saved for all prepositioning is 28 

days, but the difference between average delivery time frames for standard shipping and all 

prepositioning is 33 days.

Delivery time frames begin with WFP and USAID’s signing a grant agreement and end with the 

delivery of the food aid at the discharge port.

Data provided by WFP do not distinguish diversions from other types of shipments.

a

The coefficient is statistically significant at the 0.01 level; that is, there is a 1 percent or lower chance 

that no relationship exists between prepositioning and delivery time frames.

b

The coefficient is statistically significant at the 0.10 level; that is, there is a 10 percent or lower 

chance that no relationship exists between prepositioning and delivery time frames.

Although both overseas and domestic prepositioning shortened delivery 

time frames for WFP, the estimated time savings were larger for overseas 

prepositioning. As table 1 shows, we estimated, using statistical modeling 

to control for various factors, that prepositioning food in overseas 

warehouses saved an average of 41 days compared with USAID’s 

standard shipping process. We found that prepositioning food in domestic 

warehouses saved fewer days—an estimated average of 16.20

 

19Our analysis showed that in fiscal years 2009 through 2012, USAID directed 83 percent 

of food stored in prepositioned warehouses to WFP.

20 This estimate is statistically significant at the 10 percent level. 
 

Page 9 GAO-14-277 Prepositioning of Emergency Food Aid

We estimated, using statistical modeling to control for various factors, that 

prepositioning food aid commodities in overseas and domestic 

warehouses in fiscal years 2007 through 2012 saved an average of about 

67 days for nine of USAID’s cooperating sponsors, compared with 

USAID’s standard shipping process.21 As table 2 shows, during this 

period, the average delivery time frame for the 141 prepositioned 

shipments for these cooperating sponsors was about 87 days. In contrast, 

the average delivery time frame for the 869 standard shipments was 161 

days.22

Table 2: Estimated Days Saved by USAID’s Prepositioning of Emergency Food Aid for Nine Cooperating Sponsors, Compared 

with Standard Shipping, Fiscal Years 2007-2012

 

Number of days saved 

(regression results)

Margin of error at 

95 percent confidence (days)

Average delivery

time frame (days)

Number of 

shipments

Standard shipping - - 161 869

All prepositioning 67a 9 87 141

Overseas prepositioning 73a 9 98 52

Domestic prepositioning 62a 13 80 89

Source: GAO analysis of freight forwarder data.

Notes:

For all prepositioning, overseas prepositioning, and domestic prepositioning, we used regression 

analysis to estimate the number of days saved, controlling for factors such as commodity type and 

discharge port. As a result, the numbers of days saved do not equal the differences between average 

delivery time frames. For example, the number of days saved for all prepositioning is 67 days, but the 

difference between the average delivery time frame for standard shipping and for all prepositioning is 

74 days.

The nine cooperating sponsors are CARE, Catholic Relief Services, the government of Pakistan, 

Norwegian People’s Aid, Relief Society of Tigray, SHARE Guatemala, Save the Children, Save the 

Children—United Kingdom, and UNICEF. Data for these nine cooperating sponsors are collected and 

tracked by three freight forwarders.

Delivery time frames begin with the cooperating sponsor’s request for food aid and end with delivery 

of the requested food at the discharge port for 25 percent of the sponsors and end with delivery of the 

requested food to the recipient country for 75 percent of the sponsors.

 

21We analyzed data from three freight forwarders for the following nine cooperating 

sponsors: CARE, Catholic Relief Services, the government of Pakistan, Norwegian 

People’s Aid, Relief Society of Tigray, SHARE Guatemala, Save the Children, Save the 

Children—United Kingdom, and UNICEF. We also collected data from three freight 

forwarders that included eight of cooperating sponsors; however, we did not find these 

data to be sufficiently reliable for our purposes and did not include them in our analysis. 

See appendixes I and II for a detailed discussion of our methodology and results.

22We used regression analysis to estimate the number of days saved, controlling for 

factors such as commodity type and discharge port. As a result, the numbers of days 

saved do not equal the difference between the average delivery time frames. 

For Other Cooperating 

Sponsors, Prepositioning 

Food Aid Shortened 

Average Delivery Time 

Frame by More than 2 

Months
 

Page 10 GAO-14-277 Prepositioning of Emergency Food Aid

a

The coefficient is statistically significant at the 0.01 level—that is, there is a 1 percent or lower 

chance that no relationship exists between prepositioning and delivery time frames.

Both overseas and domestic prepositioning resulted in time savings, with 

larger savings from overseas prepositioning. As table 2 shows, after 

controlling for various factors, we estimated that prepositioning food for 

these cooperative sponsors in overseas warehouses saved an average of 

73 days relative to USAID’s standard shipping process. We also 

estimated that, relative to the standard shipping process, prepositioning 

food in domestic warehouses saved USAID an average of 62 days. 23

While prepositioning of food aid shortens delivery time frames, it has 

some disadvantages, according to one cooperating sponsor’s 

representative whom we interviewed. For example, the representative 

noted that although overseas prepositioning makes commodities 

available for immediate collection and thus saves time, handling of 

prepositioned commodities by multiple parties can lead to losses due to 

damage during the transit from prepositioning warehouse to discharge 

port. In addition, prepositioned commodities may be comingled in the 

warehouse, making it difficult to identify infestation problems in a 

particular shipment of commodities. The cooperating sponsor’s 

representative further noted that prepositioned commodities may have to 

be fumigated several times if they remain in the warehouse for months; if 

the commodities are overexposed to the fumigation chemicals, they can 

no longer be used for food aid.24

 

23 See appendix II, table 8, for disaggregation of the delivery time frames by delivery 

endpoint.

24 In reviewing a draft of this report, USAID noted that it had never experienced a situation 

where a commodity could no longer be used due to overexposure to fumigant.
 

Page 11 GAO-14-277 Prepositioning of Emergency Food Aid

We estimated, using statistical modeling to control for various factors, that 

diversion of emergency food aid from the prepositioning process 

shortened the average delivery time frame by about 64 days in fiscal 

years 2007 through 2012 compared with USAID’s standard shipping 

process (see table 3). During this period, the average delivery time frame 

for the 568 diverted shipments was about 76 days.25 In contrast, the 

average delivery time frame for the 938 standard shipments was 156 

days.26

Table 3: Estimated Days Saved by USAID’s Diversion of Prepositioning of Emergency Food Aid Shipments, Compared with 

Standard Shipping, Fiscal Years 2007–2012

 

Number of days saved 

(regression results)

Margin of error at

95 percent confidence (days)

Average delivery

time frame (days)

Number of 

shipments

Standard shipping - - 156 938

Diversiona 64b 22 76c 568

Source: GAO analysis of freight forwarders’ data.

Notes:

We used regression analysis to estimate the number of days saved, controlling for various factors 

such as commodity type and discharge port. As a result, the number of days saved does not equal 

the difference between average delivery time frames.

Delivery time frames begin with the cooperating sponsor’s request for food aid and end with delivery 

of the requested food at the discharge port for some shipments and with delivery of the requested 

food to the recipient country for other shipments.

a

The data shown for diversions were provided primarily by one freight forwarder that handles all 

USAID diversions of emergency food aid. The data include diversions of shipments for WFP and 

eight other cooperating sponsors.

b

The coefficient is statistically significant at the 0.01 level—that is, there is a 1 percent or lower 

chance that no relationship exists between prepositioning and delivery time frames.

c

This average is calculated in reference to the regression analysis.

 

25The diversions data that we collected showed that in fiscal years 2007 through 2012, 

947 shipments were designated for prepositioning warehouses and 568 (60 percent) of 

these shipments were diverted. For further details on the differences in our data sources, 

see appendix II.

26We used regression analysis to estimate the number of days saved, controlling for 

various factors such as commodity type and discharge port. As a result, the number of 

days saved does not equal the difference between the average delivery time frames. 

Diversion of Food Aid 

Intended for 

Prepositioning Shortened 

Delivery Time Frames by 

About 2 Months
 

Page 12 GAO-14-277 Prepositioning of Emergency Food Aid

According to USAID officials, prepositioning of emergency food aid allows 

for greater flexibility to divert food assistance when necessary to meet 

immediate needs. The officials further stated that, because the U.S. 

government retains ownership of prepositioned food aid, USAID does not 

have to replace diverted commodities. In contrast, when food aid is 

shipped under the standard process, non-governmental cooperating 

sponsors usually take ownership of commodities before they are shipped, 

and depending on the availability of commodities and resources, USAID 

may decide to replace diverted shipments. 

USAID has diverted commodities before and after they left the U.S. port 

and at all points in the procurement, transportation, or shipping process.27

Our analysis shows that in fiscal years 2007 through 2012, an average of 

80 days elapsed between USAID’s ordering commodities for 

prepositioning and diverting the commodities. The smallest number of 

days between USAID’s ordering and diverting commodities was 6 days, 

and the largest number of days was 163. Our analysis also shows that 

larger number of days between USAID’s ordering and diverting 

commodities are associated with shorter delivery time frames.

USAID pays additional costs for prepositioning of emergency food aid, 

compared with standard shipping. For both overseas and domestic 

prepositioning, USAID incurs additional warehouse costs that it does not 

incur for standard shipments. USAID also incurs additional shipping costs 

due to a second leg of ocean shipping from overseas prepositioning 

warehouses to foreign discharge ports. Furthermore, USAID often pays 

higher weighted annual average prices for domestically prepositioned 

commodities than it does for standard shipment commodities.28

 

27According to USAID, diversions cannot be ordered until an ocean freight carrier has 

been identified that is willing and able to deliver the diversion to the desired discharge 

port. Ocean freight contracts may include a window of time when the shipment can be 

diverted, although the terms vary by contract and carrier. USAID can request diversions 

after the window has closed, and the carrier may grant the request based on the situation. 

Some of the larger carriers allow for diversions after the commodity has been loaded on 

the ocean vessel and the vessel has set sail.

28 We calculated weighted annual average prices by dividing the total commodity cost in a 

particular year by the total commodity tonnage. The weighted averages take into account 

the quantity of the purchases, giving more weight to purchases with larger quantities.

2013 Philippines Typhoon

In November 2013, the Typhoon Haiyan 

affected 16 million people in the Philippines. 

To help meet immediate needs in the 

typhoon’s aftermath, USAID diverted 5,000 

metric tons of rice that it had purchased for its 

Colombo prepositioning warehouse and 

provided 1,020 metric tons of rice from the 

Colombo warehouse. Additionally, USAID 

airlifted approximately 55 metric tons of 

emergency food aid commodities from a 

domestic prepositioning warehouse in Miami, 

Florida. These commodities—nutrition-dense 

food bars and other items that did not require 

cooking—were sufficient to feed 15,000 adults 

and 20,000 children for 5 days.

Prepositioning 

Emergency Food Aid 

Involves Additional 

Costs
 

Page 13 GAO-14-277 Prepositioning of Emergency Food Aid

USAID incurs various additional costs to store prepositioned food in 

overseas and domestic prepositioning warehouses, depending on the 

quantity of food stored and the duration of the storage. In contrast, for 

standard shipments of emergency food aid, USAID transports the food 

directly from U.S. ports to recipient countries. The cost per day for food 

storage at USAID’s six overseas prepositioning warehouses averaged 

$0.25 per ton in fiscal years 2011 and 2012;29 the longer food is stored at 

the prepositioning warehouses, the higher the storage costs.

In fiscal years 2011 and 2012, USAID expended approximately half of the 

annual $10 million authorized by the fiscal year 2008 Farm Bill for 

overseas warehouse costs.30 Warehouse costs include, in addition to food 

storage, storage of nonfood items (e.g., bags, pallets, and cartons) and 

payment of warehouse operators for handling commodities (e.g., 

unloading trailers and loading bulk commodities). To help ensure that its 

total costs for overseas prepositioning warehouses do not exceed the 

ceiling authorized by Congress, USAID sets annual cost targets for each 

warehouse that total $8.5 million. In fiscal year 2011, USAID expended 

approximately $5.4 million—about 54 percent of its annual ceiling—for 

food storage and other costs for its overseas prepositioning warehouses. 

In fiscal year 2012, USAID expended about $4.6 million—about 46 

percent of its annual ceiling. Table 4 shows USAID’s annual targets and 

total expenditures for its overseas prepositioning warehouses in fiscal 

years 2011 and 2012.

 

29Storage costs at the six warehouses range from $0.0 per day at the Las Palmas 

warehouse to $0.49 per day at the Lomé warehouse. USAID incurs no daily storage cost 

for the Las Palmas warehouse, because storage space at the warehouse is donated by 

the Las Palmas Port Authority and the Spanish government. 

30The most recent Farm Bill which became law in February 2014 increased the ceiling to 

$15 million. Pub. L. No. 113-79, §3009.

USAID Incurs Additional 

Costs for Prepositioning 

Warehouses
 

Page 14 GAO-14-277 Prepositioning of Emergency Food Aid

Table 4: Annual Targets and Total Expenditures for USAID Overseas Prepositioning 

Warehouses, Fiscal Years 2011 and 2012

Annual targeta Fiscal year 2011 expenditures

Fiscal year 2012 

expenditures

Colombo $1,000,000 $15,282 $459,996

Djibouti 2,500,000 2,475,208 1,381,622 

Durban 2,000,000 2,783,236b 1,236,265 

Las Palmas 1,000,000 184,508 

Lomé 1,000,000 105,975 81,272

Mombasa 1,000,000 1,041 1,213,364c

Total $8,500,000 $5,380,743 $4,557,026

Source: USAID.

a

To help ensure that its total expenditures for overseas prepositioning warehouses did not exceed the 

$10 million authorized by the fiscal year 2008 Farm Bill, USAID sets annual cost ceilings for each 

warehouse.

b

Total expenditures for the Durban warehouse exceeded USAID’s annual target in fiscal year 2011. 

According to USAID, it used the Durban warehouse more than expected because of demand for 

emergency food aid from Zimbabwe and Somalia. However, USAID stayed within the overall annual 

ceiling of $10 million for 2011.

c

USAID’s expenditures at the Mombasa warehouse exceeded its annual target in fiscal year 2012. 

According to USAID, it used the Mombasa warehouse more than expected because of demand for 

emergency food aid from Somalia. However, USAID’s total overseas warehouse expenditures in 

fiscal year 2012 did not exceed the 2008 Farm Bill’s annual ceiling of $10 million.

In addition, USAID expended $2.0 million in 2011 and $3.1 million in fiscal 

year 2012 for its domestic prepositioning warehouse in Jacinto Port. 

However, these expenditures did not count against the $10 million ceiling 

set by the 2008 Farm Bill.

USAID incurs additional shipping costs when overseas prepositioning 

requires a second leg of ocean shipping, from the overseas 

prepositioning warehouses to the final discharge ports. Although the first 

leg of ocean shipping—from a U.S. port to the overseas warehouse—is 

comparable to ocean transport for standard shipping, the second leg does 

USAID Incurs Additional 

Shipping Costs for 

Overseas Prepositioning
 

Page 15 GAO-14-277 Prepositioning of Emergency Food Aid

not exist in the standard shipping process.31 For example, a prepositioned 

shipment might undergo a first leg of ocean shipping to the Djibouti 

warehouse and a second leg of ocean shipping from Djibouti to Beira, 

Mozambique; in contrast, a standard shipment would travel directly from a 

U.S. port to Beira. As table 5 shows, in fiscal year 2012, 75 percent of 

shipments from overseas prepositioning warehouses—including 100 

percent of shipments from Colombo, Las Palmas, and Lomé—traveled 

via ocean freight and thus involved costs for the second leg of ocean 

shipping. In fiscal year 2012, USAID paid a total of $13 million, averaging 

$143 per metric ton, for the second leg of ocean shipping for overseas 

prepositioned food aid.32

Table 5: Percentages and Costs of Ocean Shipping of Emergency Food Aid from Overseas Prepositioning Warehouses, 

Fiscal Year 2012

Warehouse

Total metric tons

shipped out

Metric tons shipped

by ocean freight

Percentage shipped

by ocean freight

Cost of

ocean shipping

Colombo 12,710 12,710 100% $ 6,456,255 

Djibouti 45,795 26,027 57 2,159,507

Durban 39,836 34,616 87 2,876,716

Mombasa 15,850 9,450 60 653,917 

Las Palmas 9,300 9,300 100 1,062,216 

Lomé 1,673 1,673 100 241,769 

Total 125,164 93,776 75% $ 13,450,380 

Source: GAO analysis of USAID procurement and shipping data.

 

31Because the data required to reconstruct the hypothetical cost of direct shipping for 

every prepositioned shipment were not available to us, we estimated the additional cost 

due to prepositioning using the actual cost of the second leg of ocean shipping. (See app. 

III for some examples of how the cost of the second leg of ocean shipping compares with

the estimated cost differential between prepositioning and direct shipment). In some 

cases, costs associated with the second leg of ocean shipping, from a prepositioning 

warehouse to a discharge port, might differ from the reconstructed cost differential. 

32In addition, prepositioning can increase shipping costs because of cargo preference 

requirements, which mandate that at least 50 percent of total food aid be shipped on U.S. 

flag carriers. Because of the lack of U.S. flag carriers from the overseas prepositioning 

ports, USAID has to increase the share of food aid shipped from U.S. ports on U.S. flag 

carriers in order to meet the cargo preference requirement. Because U.S. flag carriers, on 

average, have higher rates than non-U.S. flag carriers, the overall food aid shipping cost 

may therefore increase as a result of the increased use of prepositioning.
 

Page 16 GAO-14-277 Prepositioning of Emergency Food Aid

In fiscal years 2007 to 2012, USAID generally paid higher weighted 

annual average prices for commodities that it purchased for domestic 

prepositioning than for similar commodities that it purchased for standard 

shipping. Six commodities—corn-soy blend, cornmeal, pinto beans, 

vegetable oil, yellow split peas, and sorghum—accounted for 76 percent 

of USAID’s domestic prepositioning purchases in those years. Figure 2 

shows the percentage differences between the weighted annual average 

prices that USAID paid per ton for domestically prepositioned and 

standard shipment commodities in fiscal years 2007 through 2012. In 

figure 2, the bars above the zero line show that USAID paid a higher 

weighted annual average price for domestically prepositioned 

commodities in 24 instances, and the bars below the zero line show that 

USAID paid a lower weighted annual average price in 8 instances. USAID 

generally did not pay higher weighted annual average prices for overseas 

prepositioning of these commodities during this period. (See app. IV for 

more information.)

Figure 2: Percentage Differences between Weighted Annual Average Prices That USAID Paid for Six Domestically 

Prepositioned Commodities and Standard Shipment Commodities, Fiscal Years 2007-2012

Note: The graph shows the percentage differences between the weighted annual average price per 

ton for a given domestically prepositioned commodity and the weighted annual average price per ton 

for the same commodity procured for standard shipment in the same year. If the percentage 

difference is greater than 0, the weighted annual average price for the domestically prepositioned 

commodity was higher than the price for the standard shipment commodity. If the percentage 

USAID Generally Paid 

Higher Prices for 

Domestically 

Prepositioned 

Commodities Than for 

Standard Shipment 

Commodities
 

Page 17 GAO-14-277 Prepositioning of Emergency Food Aid

difference is less than 0, the weighted annual average price for the domestically prepositioned 

commodity was lower than the price for the standard shipment commodity.

HP = high performance bags.

Many factors may have contributed to the higher weighted annual 

average prices paid for domestically prepositioned commodities. For 

example, limited commodity supply and limited numbers of suppliers for 

domestic prepositioning purchases are two possible factors, according to 

U.S. officials and commodity vendors whom we interviewed.33 First, if 

USAID purchases commodities for domestic prepositioning after 

commodity vendors have fulfilled their monthly orders for standard 

shipment and overseas prepositioning, vendors may have a reduced 

supply of commodities available for domestic prepositioning and may 

therefore charge higher prices. Second, because domestically 

prepositioned commodities—unlike standard shipment and overseas 

prepositioned commodities—are delivered to only two preselected U.S. 

ports, vendors for some commodities may be unwilling to compete with 

vendors who are geographically closer to the port and who thus can 

deliver the commodities to the port more cheaply.

USAID has taken some steps to evaluate timeliness and costs associated 

with prepositioning. However, the agency does not collect and assess 

data needed to systematically monitor delivery time frames for 

prepositioned commodities to maximize time savings. Further, USAID 

does not systematically monitor the costs of prepositioning to maximize 

the program’s cost-effectiveness. According to USAID guidance, the 

agency should monitor programs through various activities, including 

collecting and analyzing data to make necessary program adjustments 

and to guide higher-level decision making and resource allocation.

Additionally, federal internal control standards indicate that monitoring 

should assess the quality of performance over time and ensure that the 

findings of these assessments are promptly resolved.34

 

33In addition to these two factors, other reasons, such as the frequency of purchases, may 

account for the differences between the weighted annual average prices for domestically 

prepositioned commodities and for standard shipment commodities. See appendix IV for 

the number of annual purchases of domestically prepositioned commodities.

34 See GAO, Standards for Internal Control in the Federal Government, 

GAO/AIMD-00-21.3.1 (Washington, D.C.: November 1999). 

USAID Does Not 

Systematically 

Monitor 

Prepositioning to 

Maximize Time 

Savings and Cost 

Effectiveness
 

Page 18 GAO-14-277 Prepositioning of Emergency Food Aid

USAID has taken some steps to evaluate prepositioning of emergency 

food aid by examining timeliness and costs. For example, in 2008, USAID 

commissioned a cost-benefit analysis of prepositioning.35 The analysis 

found that prepositioning food aid reduced delivery time frames of 

emergency shipments from an average of 177 days for standard 

shipments of food aid to an average of 26 days. The analysis also found 

that the average cost for domestically prepositioned food aid amounted to 

an additional $23 per metric ton, and the average cost for overseas 

prepositioned food aid amounted to an additional $164 per metric ton. 

However, the methodology for the 2008 analysis had several limitations. 

First, the analysis did not include data on delivery time frames for WFP, 

USAID’s largest cooperating sponsor for emergency food aid. Second, 

the analysis included data on delivery time frames up to the date when 

the shipments were discharged at the foreign ports but did not include 

any data up to the date when the shipments arrived in the recipient 

countries. Third, the evaluation did not compare shipments of 

prepositioned food with standard shipments that had similar 

characteristics, such as the recipient country. Because differences in 

such characteristics can contribute to differences in delivery time frames, 

the evaluation may not have accurately isolated the effects of 

prepositioning.

In 2009, USAID also developed a framework for prepositioning that 

outlines the purpose of the program. However, the framework is not upto-date and does not guide current prepositioning practices, according to 

USAID officials. Additionally, the framework does not outline guidelines 

for evaluations on timeliness or costs.

In 2013, USAID’s Inspector General found that the agency had not 

determined whether the benefits of overseas prepositioning in the Horn of 

Africa outweighed the costs and whether overseas prepositioning saved

time compared with domestic prepositioning. The report recommended, 

among other things, that USAID conduct another independent evaluation 

of the cost and timeliness of prepositioning.36 In November 2013, USAID 

released a solicitation for a third-party vendor to conduct an independent 

 

35Janet R. van der Vaart, P.L. 480 Title II Pre-positioning Cost/Benefit Analysis (2008). 

36U.S. Agency for International Development, Office of Inspector General, Audit of 

USAID’s Internal Controls Over Prepositioned Food Assistance for the Horn of Africa, 

Audit Report No. 4-962-13-004-P ( Jan. 7, 2013). 

USAID Has Taken Some 

Steps to Evaluate 

Prepositioning
 

Page 19 GAO-14-277 Prepositioning of Emergency Food Aid

evaluation of prepositioning; the contract was awarded in January 2014. 

According to USAID, the evaluation will be finalized in March 2014 and 

will include an analysis of the cost, benefits, and effectiveness of 

prepositioning.37

Although USAID’s goal for prepositioning is to improve the timeliness of 

emergency food aid, USAID does not collect or assess data needed to 

systematically monitor delivery time frames for prepositioned emergency 

food aid shipments. According to guidance in USAID’s Automated 

Directives System, the agency should monitor programs through various 

activities, including collecting and analyzing data to make necessary 

program adjustments and to guide higher-level decision making.38

Moreover, USAID’s evaluation policy states that programs can best 

manage for results by collecting and analyzing information to track 

progress toward planned results and by ensuring that implementing 

partners collect relevant monitoring data. The policy also states that 

monitoring can reveal whether desired results are occurring and whether 

implementation is on track.39

USAID officials told us that the agency would be able to calculate delivery 

time frames of prepositioned food only if its cooperating sponsors 

provided data on all emergency food aid shipments. According to the 

officials, these sponsors are responsible for tracking food shipments once 

the shipments leave U.S. loading ports. However, according to USAID, 

the terms of its agreements with its cooperating sponsors do not require 

these sponsors to collect or provide comprehensive data to USAID. As a 

result, USAID lacks the ability to determine whether prepositioning is 

achieving its primary goal of shortening response times or to identify 

possible time savings relative to standard emergency food aid shipments.

In addition, some emergency food aid data that are currently available 

from WFP and USAID’s other cooperating sponsors have limitations that 

 

37The contract specifies that a draft of the evaluation will be available 60 days from the 

start of the contract.

38U.S. Agency for International Development, Automated Directives System (ADS) 

Chapter 203: Assessing and Learning (Washington D.C.: Feb. 10, 2012).

39U.S. Agency for International Development, USAID Evaluation Policy (Washington D.C.: 

January 2011).

USAID Does Not Collect 

and Assess Data Needed 

to Systematically Monitor 

Delivery Time Frames for 

Prepositioned 

Commodities
 

Page 20 GAO-14-277 Prepositioning of Emergency Food Aid

constrain their usefulness for monitoring delivery time frames. We 

collected data on emergency food aid shipments, including prepositioned 

shipments, from 19 cooperating sponsors; however, because of the 

following limitations, we did not include some of these data in our analysis 

of delivery time frames.

• Limitations in WFP data. We did not use data provided by WFP for 

our analysis of diversion’s effect on delivery time frames, because 

WFP’s data on emergency food aid shipments do not distinguish 

diversions from other standard or prepositioned shipments. WFP also 

was unable to provide data for years before 2009 because of changes 

in its data management systems. As a result, we used data provided 

by a freight forwarder for our analysis of WFP diversions.

• Limitations in some data from several other cooperating 

sponsors. Some data from five cooperating sponsors that received 

emergency food aid in fiscal years 2007 through 2012 do not 

distinguish emergency food aid shipments from other types of food aid 

shipments. In addition, some data for these five cooperating sponsors 

and three others were incomplete, missing some shipments and 

providing only partial information for others. As a result, we were 

unable to use some of the data from these eight sponsors.

Although USAID collects data on the cost of its international food aid 

programs, it does not use these data to systematically monitor the total 

cost of prepositioning in order to maximize the program’s cost 

effectiveness. According to USAID’s Automated Directives System, the 

agency should collect and analyze data to make necessary program 

adjustments and to guide higher-level decision making and resource 

allocation.40 Further, federal internal controls indicate that monitoring 

should assess the quality of performance over time and ensure that the 

findings of these assessments are promptly resolved. USAID collects 

data on the total costs of its overseas prepositioning warehouses to 

ensure that the costs do not exceed the limit established by Congress.41

However, USAID does not analyze this information to determine whether 

the locations of these warehouses are cost effective. Further, the agency 

 

40U.S. Agency for International Development, Automated Directives System (ADS), 

Chapter 203.

41See 7 U.S.C. § 1736a(c)(4)(A).

USAID Does Not 

Systematically Monitor the 

Total Cost of 

Prepositioning to 

Maximize Cost 

Effectiveness
 

Page 21 GAO-14-277 Prepositioning of Emergency Food Aid

does not systematically or routinely monitor and analyze prepositioning 

commodity and shipping costs to determine the cost-effectiveness of 

prepositioning.42

USAID collects data on prepositioning commodity and shipping costs, 

according to agency officials. However, USAID does not store these data 

in a single system or spreadsheet, where they would be easily accessible 

for monitoring purposes. Instead, according to USAID, various offices 

collect these data and store them in a number of different systems or 

spreadsheets.43 In addition, agency officials told us that because 

prepositioning is not a separate program but is part of USAID’s 

emergency food aid program, the agency does not monitor prepositioning 

costs separately. These officials also stated that the agency does not 

monitor prepositioning’s total costs, because the primary goal of 

prepositioning is rapid response rather than financial savings.

As a result of the lack of monitoring of prepositioning costs, USAID does 

not conduct analyses that could help it manage its resources and improve 

the program’s cost-effectiveness. For example, the agency does not know 

the causes of the commodity price differences that we identified and 

therefore is limited in its ability to ensure that the procurement of 

prepositioned commodities is conducted in a cost-effective manner.

The emergency food aid that USAID provides helps to save lives in 

countries where ongoing or unanticipated crises have severely disrupted 

food supplies. Our analysis of prepositioning showed that this approach 

can have a significant effect on the United States’ and its cooperating 

sponsors’ ability to deliver food quickly in response to humanitarian 

emergencies. However, without reliable data on the delivery time frames 

of prepositioned shipments, USAID lacks management tools that could 

help it assess and improve prepositioning’s effect on emergency 

response times. Such data could also help USAID assess the tradeoffs 

between prepositioning’s timeliness and its additional warehouse, 

shipping, and commodity costs. Furthermore, although cost savings are 

 

42According to USAID, an upcoming independent evaluation on prepositioning will analyze 

the cost effectiveness of prepositioning.

43According to USAID, all contracts related to the costs of the prepositioning program are 

reviewed and evaluated by USAID contracting officials.

Conclusions
 

Page 22 GAO-14-277 Prepositioning of Emergency Food Aid

not USAID’s primary goal for the prepositioning program, without 

systematic monitoring of the total cost of prepositioning the agency has 

limited ability to maximize the resources available for addressing 

emergency food crises.

To strengthen USAID’s ability to help ensure that its food aid 

prepositioning program meets the goal of reducing delivery time frames in 

a cost-effective manner, we recommend that the USAID Administrator 

take the following three steps to systematically

1. collect, and ensure the reliability and validity of, data on delivery time 

frames for all emergency food aid shipments, including prepositioned 

food aid shipments;

2. monitor and assess data on delivery time frames for prepositioned 

food aid shipments; and

3. monitor and assess costs associated with commodity procurement, 

shipping, and storage for prepositioned food aid shipments.

We provided a draft of this report for comment to USAID.

USAID provided written comments on a draft to this report, which we 

reprinted in appendix VI. In its comments, USAID concurred with our 

recommendations. In addition, USAID stated that it is working to identify 

actions needed to ensure the collection of reliable data on delivery time 

frames for all emergency food aid. USAID also stated that it is revising its 

prepositioning program strategy to provide a framework for monitoring 

and assessing data on the timeliness and cost effectiveness of the 

prepositioning program. 

In addition to providing copies of this report to your offices, we will send 

copies to interested congressional committees. We will make copies 

available to others on request. In addition, the report will be available at 

no charge on the GAO Web site at http://www.gao.gov. 

If you or your staff have any questions regarding this report, please 

contact me at (202) 512-9601 or MelitoT@gao.gov. Contact points for our 

Offices of Congressional Relations and Public Affairs may be found on 

Recommendations for 

Executive Action

Agency Comments
 

Page 23 GAO-14-277 Prepositioning of Emergency Food Aid

the last page of this report. GAO staff who made key contributions to this 

report are listed in appendix VI.

Sincerely yours,

Thomas Melito

Director, International Affairs and Trade
Appendix I: Objectives, Scope, and 

Methodology

Page 24 GAO-14-277 Prepositioning of Emergency Food Aid

We examined (1) the effects of USAID’s prepositioning on delivery time 

frames for emergency food aid shipments, (2) the effects of prepositioning 

on the costs of emergency food aid, and (3) the extent to which the 

agency monitors prepositioning to manage program resources effectively.

To examine the effects of prepositioning on delivery time frames, we 

collected shipment-level data from the World Food Program (WFP) and 

six freight forwarders for 19 other cooperating sponsors.1 We assessed 

the reliability of these data by asking WFP and the six freight forwarders 

how the data were collected, what quality checks were performed, and 

what other internal controls were in place. We determined that the data 

were sufficiently reliable for tracking the delivery time frames of 

emergency food aid for WFP and three of the freight forwarders that 

manage the food aid supply chain for nine cooperating sponsors. For the 

remaining three freight forwarders, the data were not sufficiently reliable 

for tracking delivery time frames because of a number of limitations, 

including incomplete or missing data and, in one freight forwarder’s data, 

a lack of distinction between emergency and nonemergency shipments.

The data that we included in our analysis of the effects of prepositioning 

on delivery time frames include the date when the cooperating sponsor 

requested the food (or the closest approximation) 2 and the date when the 

 

1

Cooperating sponsors are organizations that have received USAID grants for delivery of 

emergency food aid to recipient countries. Freight forwarders are contractors that manage 

USAID’s and other cooperating sponsors’ food aid supply chain. WFP, which is also a 

cooperating sponsor, maintains its own shipment data and was able to provide this 

information.

2

Data provided by WFP and the three freight forwarders approximate the dates when the 

cooperating sponsors requested the food from USAID. Data provided from one of the 

three freight forwarders included the date when USAID approved the request, up to a few 

weeks afterward. This should not affect our estimates of days saved. According to USAID, 

the number of days between the request for food and USAID’s approval date is similar for 

prepositioned and standard shipments. WFP’s data provide the date when WFP and 

USAID signed a grant agreement, which could be 5 days or less before the date when 

WFP requested the food. However, both USAID and WFP officials noted that whether a 

shipment was sourced from a prepositioning warehouse or the standard shipping process 

did not affect the number of days between the request for food date and USAID’s grant 

agreement date. Therefore, in comparisons of prepositioned and standard shipments, the 

days between the request for food and USAID’s grant agreement should not affect our 

estimates of days saved by prepositioning.

Appendix I: Objectives, Scope, and 

Methodology
Appendix I: Objectives, Scope, and 

Methodology

Page 25 GAO-14-277 Prepositioning of Emergency Food Aid

food arrived at the discharge port or in the recipient country.3 In addition, 

the data indicate whether the shipment was from prepositioning. The data 

also include other shipment characteristics—for example, the loading 

port, the discharge port, and the commodity shipped—and indicate 

whether the shipment was an emergency or nonemergency shipment and 

whether it was bulk or packaged.

We separately discuss our analysis of data provided by WFP and the 

other cooperating sponsors’ three freight forwarders because WFP’s and 

these freight forwarders’ data differ in the time periods covered and their 

treatment of food aid diversions.

• Time periods covered. Data provided by WFP cover shipments in 

fiscal years 2009 through 2012, while data provided by the three 

freight forwarders cover shipments in fiscal years 2007 through 2012.

• Treatment of food aid diversions. Data provided by WFP do not 

distinguish shipments that USAID diverted from the prepositioning 

process from shipments that it prepositioned, while data provided by 

the freight forwarders do identify diversions. Despite this difference, 

our analysis suggests that using WFP’s data to estimate the number 

of days saved from prepositioning would not have affected our 

estimates significantly.

To analyze delivery time frames, we calculated the number of days 

between a cooperating sponsor’s request for the commodities and the 

commodities’ arrival at the discharge port or in the recipient country. To 

compare delivery time frames for overseas and domestic prepositioning 

with those for standard shipping for WFP and for other cooperating 

sponsors, we estimated ordinary least squares regression models to 

 

3

Data provided by WFP include only the date of the shipment’s arrival at the discharge 

port. Data provided by the freight forwarders include the date of arrival at the discharge 

port for some shipments and the date of arrival in the recipient country for others (even if 

the discharge port was outside the recipient country). While the average delivery time 

frames differ for shipments with the date of arrival in the recipient country compared with 

shipments with the date of arrival at the discharge port, we did not find evidence that 

combining these shipments would affect our estimates of number of days saved from 

prepositioning; inland transport from the discharge port to the recipient country is similar 

for prepositioned and standard shipments. See table 8 in appendix II for average delivery 

time frames for shipments with the date of arrival at the discharge port and in the recipient 

country. 
Appendix I: Objectives, Scope, and 

Methodology

Page 26 GAO-14-277 Prepositioning of Emergency Food Aid

control for characteristics of prepositioning and standard shipments that 

would allow us to isolate the effect of prepositioning.4

To examine the effects of USAID’s diversions of emergency food aid 

shipments on delivery time frames, we used data primarily from the 

freight forwarder responsible for tracking all diverted shipments for World 

Food Program (WFP) and for eight other cooperating sponsors.5 This 

freight forwarder’s data include all diverted food aid shipments from fiscal 

years 2007 through 2012. For the comparison group of standard 

shipments, we used data from this freight forwarder in addition to data 

from two other freight forwarders. We determined that these data were 

sufficiently reliable for tracking delivery time frames. Like the data that we 

included in our analysis for prepositioning, the diversions data are at the 

shipment level and include the date when WFP and other cooperating 

sponsors requested the food (or the closest approximation)6 and the date 

when the food arrived at the discharge port or in the recipient country. In 

addition, the data indicate whether the shipment was diverted. The data 

also include other shipment characteristics—for example, the loading 

port, the discharge port, and the commodity shipped—and indicate 

whether the shipment was bulk or packaged and was an emergency or 

nonemergency shipment. GAO analysts collected the dates USAID 

authorized food aid diversions by reviewing one freight forwarder’s 

shipment documents.7

 

4

See appendix II for further details and results of the regression models.

5

While almost all diversion data analyzed were provided by one freight forwarder 

responsible for tracking all diverted shipments, data for 39 diverted shipments were 

analyzed using data from two other freight forwarders because their information better 

approximated the date the cooperating sponsors requested food. Cooperating sponsors 

included in the diversion data are ACDI/VOCA, Adventist Development and Relief Agency, 

CARE, Counterpart International, Catholic Relief Services, Food for the Hungry, Save the 

Children–U.S, and World Vision. 

6

For diversions, when the date of the cooperating sponsor’s request for the food was 

unavailable, we used as an approximation the date when USAID authorized the diversion. 

According to USAID, USAID generally authorizes diversions a few days after the 

cooperating sponsor requests the food. 

7 While we may have introduced measurement error to the regression model with our data 

collection, measurement error should not affect our estimate of the number of days saved 

from diversions compared with standard shipments.
Appendix I: Objectives, Scope, and 

Methodology

Page 27 GAO-14-277 Prepositioning of Emergency Food Aid

To analyze additional costs associated with prepositioning, we looked at 

three types of cost that are unique to prepositioned food: costs for 

prepositioning warehouses, costs for ocean shipping from overseas 

prepositioning warehouses to discharge ports, and costs for procurement 

for prepositioning commodities.

• Warehouse costs. To analyze prepositioning warehouse costs, we 

obtained warehouse contracts from USAID. Each contract identifies 

the annual expenditure target that USAID had established for the 

warehouse as well as the daily storage charge per metric ton and 

outlines other charges related to handling the commodities.

• Ocean shipping costs. We estimated the additional cost due to 

prepositioning using the actual cost of the second leg of ocean 

shipping, because the data required to re-construct the hypothetical 

cost of direct shipping for every prepositioned shipment were not 

available to us. Although the first leg of ocean shipping—from a U.S. 

port to the overseas warehouse—is comparable to ocean transport for 

standard shipping, the second leg does not exist in the standard 

shipping process.8 We obtained data from USAID that track the mode

of transportation of shipments from each of the overseas warehouses, 

the metric tonnage, and the freight cost. (See app. III for examples of 

the additional ocean transportation costs.)

• Commodity procurement costs. To analyze prepositioning 

commodity procurement costs, we focused on six commodities that 

accounted for 76 percent of total prepositioning purchases. We 

compared the weighted annual average prices of commodities 

purchased for domestic prepositioning, overseas prepositioning, and 

standard shipping. To understand the possible reasons for the 

observed differences in prices for prepositioned commodities, we 

interviewed U.S. Department of Agriculture (USDA) officials as well as 

commodity vendors. (See app. IV for the results of the price 

comparison.).

To examine the extent to which USAID monitors prepositioning to 

maximize time savings and cost effectiveness, we reviewed USAID 

 

8

In some cases, costs associated with the second leg of ocean shipping, from a 

prepositioning warehouse to a discharge port, might not be the same as the reconstructed 

cost differential. 
Appendix I: Objectives, Scope, and 

Methodology

Page 28 GAO-14-277 Prepositioning of Emergency Food Aid

documentation related to prior, current, and future efforts to monitor its 

prepositioning program, specifically efforts to monitor the delivery time 

frames and program costs. We also interviewed USAID officials in 

Washington, D.C., to discuss the extent to which the agency has taken 

steps to monitor the program. We also interviewed WFP, one other 

cooperating sponsor, and freight forwarders in Washington, D.C. We 

reviewed evaluations and reports on USAID’s prepositioning, such as a 

2008 evaluation of the program and a 2013 USAID Inspector General 

report on prepositioning.9 Using USAID criteria, we evaluated USAID’s 

efforts to monitor its prepositioning program.10 We also analyzed and 

assessed the reliability of data on emergency food aid shipments that we 

collected from cooperating sponsors’ freight forwarders to determine 

whether these data could be used to monitor delivery time frames of 

prepositioned food. We found that the data provided by three freight 

forwarders were not sufficiently reliable for tracking delivery time frames 

for emergency food aid shipments owing to a number of limitations, 

including incomplete or missing data and, in one freight forwarder’s data, 

lack of distinction between emergency and nonemergency shipments. We 

also reviewed relevant legislation to determine where there are any 

statutory requirements to monitor or evaluate USAID’s prepositioning 

program.

We conducted this performance audit from July 2013 to March 2014 in 

accordance with generally accepted government auditing standards. 

Those standards require that we plan and perform the audit to obtain 

sufficient, appropriate evidence to provide a reasonable basis for our 

findings and conclusions based on our audit objectives. We believe the 

evidence obtained provides a reasonable basis for our findings and 

conclusions based on our audit objectives.

 

9

Janet R. van der Vaart, P.L. 480 Title II Pre-positioning Cost/Benefit Analysis (2008);and 

U.S. Agency for International Development, Office of Inspector General, Audit of USAID’s 

Internal Controls Over Prepositioned Food Assistance for the Horn of Africa, Audit Report 

No. 4-962-13-004-P (Jan. 7, 2013). 

10U.S. Agency for International Development, Automated Directives System (ADS) 

Chapter 203: Assessing and Learning (Washington D.C.: Feb.10, 2012); USAID 

Evaluation Policy (Washington D.C.: January 2011).
Appendix II: Delivery Time Frames Regression 

Analysis

Page 29 GAO-14-277 Prepositioning of Emergency Food Aid

A variety of factors besides prepositioning and food aid diversions may 

affect delivery time frames, therefore we developed a statistical model—a 

linear regression model—to control for factors that are likely to be 

associated with delivery time frames, helping to isolate the effect of 

prepositioning and food aid diversions.

We collected shipment data from the WFP and six freight forwarders.1

The data indicate whether the shipment was from prepositioning or was 

standard and include the date (or the closest approximation) when the 

cooperating sponsor requested the food,2 the date of the food’s arrival at 

the discharge port or in the recipient country, and other shipment 

characteristics such as the commodity shipped. We assessed the 

reliability of these data by asking WFP and the six freight forwarders how 

the data were collected, what quality checks were performed, and 

whether other internal controls were in place. We determined that the 

data from WFP and three of the freight forwarders3

—74 percent of the 

data we collected—were sufficiently reliable for tracking delivery time 

frames and comparing standard, prepositioning, and diverted shipments. 

Table 6 shows the numbers of prepositioned, standard, and diverted 

shipments represented in the data that we deemed sufficiently reliable for 

our analysis.

 

1

In fiscal years 2007 through 2012, seven freight forwarders managed USAID’s and its 

cooperating sponsors’ supply chain. We collected data from six of these contractors; we 

did not collect data from WFP’s freight forwarder, instead collecting data directly from 

WFP. We did not include in our analysis data from three of the other six freight forwarders, 

because we found that data were incomplete or missing in these three contractors’ data 

and we could not distinguish emergency from nonemergency shipments in one of these 

contractors’ data.

2

See appendix I for a discussion of dates included in WFP and the freight forwarders’ 

data.

3

These three freight forwarders manage the Title II emergency food aid supply chain for 

nine of USAID’s cooperating sponsors.

Appendix II: Delivery Time Frames 

Regression Analysis

Data Sources
Appendix II: Delivery Time Frames Regression 

Analysis

Page 30 GAO-14-277 Prepositioning of Emergency Food Aid

Table 6: Numbers of Emergency Food Aid Shipments Represented in Data Included in GAO Analysis

Data source

Number

of shipments

Percentage

of total

Prepositioning

shipments

Standard

shipments

Included in GAO analysis

WFP 2,137 42 472 1,665

Three freight forwardersa 1,010 20 141 869

Diverted shipmentsb 568 11

WFP shipmentsc 70 1 

Subtotal 3,785 74 613 2,603

Not included in GAO analysis 1,357 26

Total shipments represented 5,142

Source: GAO analysis of WFP’s and freight forwarders’ data.

Notes:

a

The three forwarders manage the Title II emergency food aid supply chain for nine of USAID’s 

cooperating sponsors.

b

WFP’s data do not identify diversions from other types of shipments.

c

One freight forwarder included data on 69 standard shipments and 1 domestically prepositioned 

shipment for WFP.

We excluded shipments from our analysis that were outside our scope,4

were duplicated in two freight forwarders’ data, or did not have a 

discernible delivery time frame. In addition, we found data from the 

remaining three freight forwarders to be insufficiently reliable for tracking 

delivery time frames of emergency food aid owing to a number of 

limitations, including incomplete or missing data and, in one freight 

forwarder’s data, a lack of distinction between emergency and 

nonemergency shipments. Table 7 shows the number of shipments that 

we excluded from our analysis and the reasons for their exclusion.

 

4

These shipments include shipments ordered in fiscal year 2013 and shipments ordered 

by USAID for the prepositioning warehouses. Shipments ordered for the prepositioning 

warehouses do not fulfill a cooperating sponsor’s request; instead, their contents are 

stored in prepositioning warehouses and are later used to fulfill cooperating sponsors’ 

requests.
Appendix II: Delivery Time Frames Regression 

Analysis

Page 31 GAO-14-277 Prepositioning of Emergency Food Aid

Table 7: Numbers of Emergency Food Aid Shipments Represented in Data 

Excluded from GAO Analysis and the Reasons for Exclusion

Reason for exclusion Number of shipments

Outside our scopea 572

Duplicate shipmentsb 29

Shipment with indiscernible delivery time frame 1 

Not sufficiently reliable 755

Total 1,357

Source: GAO analysis of WFP’s and freight forwarders’ data.

a

These shipments include shipments ordered in fiscal year 2013 and shipments ordered by USAID for 

the prepositioning warehouses. Shipments ordered for the prepositioning warehouses do not fulfill a 

cooperating sponsor’s request, but instead comprise the food stored in prepositioning warehouses 

that are later used to fulfill cooperating sponsors’ requests.

b

These shipments were included in two freight forwarders’ data, but are more accurately captured in 

one set of data. We then exclude the duplicate shipments in the other set of data.

We separately analyzed data provided by WFP and the three freight 

forwarders that we included in our analysis, because the two groups of 

data differ in the time periods covered and their treatment of food aid 

diversions. WFP’s data cover shipments in fiscal years 2009 through 

2012, while the three freight forwarders’ data cover shipments in fiscal 

years 2007 through 2012. In addition, WFP’s data do not distinguish 

between diversions of food aid and other shipments, preventing our 

estimation of the number of days saved from diversions of food aid using 

WFP’s data.

We also separately analyzed the effect of food aid diversions on delivery 

time frames. All food aid diversions, including diversions to WFP’s 

programs, are managed by one freight forwarder.5 For a comparison 

group, we used standard shipments included in the three freight 

forwarders’ data.6 We did not include WFP’s data in the comparison 

group because of the differences between WFP’s and the three freight 

forwarders’ data. GAO analysts collected the dates USAID authorized 

 

5

 Almost all of the diversion data that we analyzed were provided by one freight forwarder 

responsible for tracking all diverted shipments. However, for 39 diverted shipments, we 

analyzed data provided by two other freight forwarders, because these data better 

approximated the date when the cooperating sponsors requested food.

6

One freight forwarder’s data include 69 standard shipments and 1 shipment from 

domestic prepositioning that were destined for WFP’s programs, which we also included in 

the comparison group.
Appendix II: Delivery Time Frames Regression 

Analysis

Page 32 GAO-14-277 Prepositioning of Emergency Food Aid

food aid diversions by reviewing one freight forwarder’s shipment 

documents.7

Because of differences between the data sources, we used slightly 

different start and end dates to estimate delivery time frames. In addition, 

our results from the linear regression model do not cover 2007 and 2008 

for WFP’s shipments or other freight forwarders’ shipments not included 

in our analysis.

• Start dates. Although we defined delivery time frame as the number 

of days between a cooperating sponsor’s request for food and arrival 

at a discharge port or recipient country, the start dates we collected 

were the best available approximations of the date of request and 

differed slightly in data provided by WFP and the freight forwarders. 

However, USAID and WFP officials stated that the number of days 

between the start dates and WFP’s food request dates does not differ 

for prepositioning and standard shipments. USAID and freight 

forwarder officials also stated that the number of days between the 

freight forwarder start dates and the dates they request the food does 

not differ for prepositioning and standard shipments. For comparisons 

of prepositioning and standard shipments, the difference between the 

start dates we collected and the request dates should not affect our 

results. However, these differences may affect the average delivery 

time frames we calculated, which should be considered as context for 

our regression analysis rather than exact estimates. For diversions, 

we also used the best available approximations of the date of 

request—usually the date when USAID authorized the diversion. 

According to USAID officials, the authorization date is generally a few 

days after the request date. Therefore, for comparisons of diversions 

and standard shipments, our estimates should be accurate to within a 

few days.

• End dates. Data provided by WFP include only the date of the food’s 

arrival at the discharge port. Data provided by the freight forwarders 

include, for some freight forwarders, only the date of the food’s arrival 

at the discharge port for some shipments and, for other freight 

 

7 While our data collection may have introduced measurement error to the regression 

model, measurement error should not affect our estimate of the number of days saved by

diversions compared with standard shipments.

Limitations
Appendix II: Delivery Time Frames Regression 

Analysis

Page 33 GAO-14-277 Prepositioning of Emergency Food Aid

forwarders, only the date of the food’s arrival in the recipient country 

when inland transportation is required. Although this affects the 

average delivery time frames we calculated, it should be considered 

as context for our regression analysis rather than exact estimates. 

Moreover, we found that combining these shipments did not affect our 

regression estimates of number of days saved from prepositioning; 

inland transport from the discharge port to the recipient country is 

similar for prepositioned and standard shipments. In addition, we 

controlled for the port of arrival (either a discharge port or in the 

recipient country) in our analysis. See table 8 for average delivery 

time frames for shipments with dates of arrival at the discharge port 

and in the recipient country.

• Treatment of diversions. Data provided by WFP do not distinguish 

diversions from standard or prepositioning shipments. However, we 

estimate that this limitation may affect our estimates of number of 

days saved by prepositioning by only a few days.8

• Nongeneralizable results. Our estimates are not generalizable 

beyond the time periods covered by the data (fiscal years 2009 

through 2012 for data provided by WFP and fiscal years 2007 through 

2012 for the data provided by the freight forwarders) or beyond WFP 

and the three freight forwarders’ data that we included in our analysis.

Table 8 shows the average delivery time frames for two groups of 

emergency food aid shipments. The first group comprises shipments 

shown in WFP’s data, with delivery time frame defined as the number of 

days between the date when WFP and USAID signed a grant agreement 

and the date when the shipment arrived at the discharge port. The 

second group comprises shipments shown in the freight forwarders’ data, 

with the delivery time frame defined as the number of days between the 

date when the cooperating sponsor requested the food and the date 

when the shipment arrived at the discharge port or recipient country.

 

8

To estimate the effect of this limitation on our results for WFP, we estimated the amount 

of commodities diverted to WFP programs using data from the freight forwarder that tracks 

all diversions. We made the conservative assumption that all of these diversions are 

standard shipments in WFP’s data. Using the estimated number of days saved by 

diversions, based on the freight forwarders’ data, we were then able to estimate the bias 

introduced by this limitation.

Average Delivery Time 

Frames
Appendix II: Delivery Time Frames Regression 

Analysis

Page 34 GAO-14-277 Prepositioning of Emergency Food Aid

Table 8: Average Delivery Time Frames (in Days) for Emergency Food Aid Shipments

 

Standard 

shipments

All prepositioning 

shipments

Overseas 

prepositioning 

shipments

Domestic 

prepositioning 

shipments

WFP (fiscal years 2009-2012)a

Average delivery time frame 135 102 92 114

Number of shipments 1,665 472 262 210

Three freight forwarders (fiscal years 2007-2012)

Data with date of arrival in the recipient country (includes land transport)

Average delivery time frame 170 110 103 120

Number of shipments 681 79 47 32

Data with date of arrival at the discharge port (does not include land transport)

Average delivery time frame 129 58 54 58

Number of shipments 188 62 5 57

Source: GAO analysis of WFP’s and three freight forwarders’ data.

Note: The three forwarders manage the Title II emergency food aid supply chain for nine of USAID’s 

cooperating sponsors.

a

Data provided by WFP do not identify diversions from other types of shipments.

To isolate the effect of prepositioning on delivery time frames for 

emergency food aid, we estimated ordinary least squares regression 

models that control for characteristics of prepositioned and standard 

shipments for WFP and for the nine other cooperating sponsors 

represented in the three freight forwarders’ data. Tables 9 and 10, 

respectively, show the results of our regression analysis of the data 

collected from WFP and the three freight forwarders, demonstrating the 

average number of days saved by prepositioning relative to standard 

shipping delivery time frames. Specifically, we estimated Yi = α + βPrepoi

+ δXi + εi for the second column in each table, where Yi is the delivery 

time frame of shipment i, Prepoi is a dummy for whether shipment i is 

from prepositioning, and Xi are the control variables listed in column 1. 

We estimated Yi = α + β1DomesticPrepoi + β2OverseasPrepoi + δXi + εi

for the third column, where Yi is the delivery time frame of shipment i, 

DomesticPrepoi is a dummy for when shipment i is from domestic 

prepositioning, OverseasPrepoi is a dummy for when shipment i is from 

overseas prepositioning, and Xi are the control variables listed in

Prepositioning
Appendix II: Delivery Time Frames Regression 

Analysis

Page 35 GAO-14-277 Prepositioning of Emergency Food Aid

column 1.9 We clustered the standard errors by the discharge port or 

recipient country. For WFP, we included the discharge port, the year of 

the commodity request, the month of the commodity request, and the 

commodity type as control variables. For the nine cooperating sponsors, 

we included the freight forwarder, the cooperating sponsor, the discharge 

port or recipient countries, the year of the commodity request, the month 

of the commodity request, and the commodity type as control variables. 

These variables are known to USAID when cooperating sponsors submit 

requests for commodities.10 Controlling for these variables allowed us to 

compare shipments that fulfilled requests with similar characteristics. We 

did not control for the shipment’s tonnage, the port of loading, and other 

variables that USAID determines when it decides whether to fulfill a 

sponsor’s request with commodities sourced from the standard shipping 

process or from prepositioned warehouses.11

Table 9: Estimated Days Saved by USAID’s Prepositioning Emergency Food Aid for the World Food Program, Relative to 

Standard Shipping, Fiscal Years 2009- 2012

 Prepositioning regression 

Domestic and overseas

prepositioning regression

Coefficients and standard errors for prepositioning 

Prepositioning (domestic or overseas) -27.504*** 

Standard error <7.419> 

Domestic prepositioning -15.652***

Standard error <8.497> 

Overseas prepositioning -40.692***

Standard error <8.258> 

Sample size 2137 2137

 

9

These regression results are robust to removing outliers and influential shipments.

Removing the slowest and fastest shipments and influential shipments yields similar 

regression results. In addition, estimating a propensity score matching model yields similar 

results.

10Cooperating sponsors’ requests also include the tonnage requested. However, USAID 

decides how much tonnage to include in each shipment when it decides whether to source 

the shipment from the standard shipping process or prepositioned warehouses. USAID 

may source part of the request from prepositioned warehouses and the rest from the 

standard shipping process. 

11We estimated models controlling for the shipment’s tonnage and the flag of the ocean 

vessel which yielded similar regression results.
Appendix II: Delivery Time Frames Regression 

Analysis

Page 36 GAO-14-277 Prepositioning of Emergency Food Aid

 Prepositioning regression 

Domestic and overseas

prepositioning regression

Adjusted R squared 0.36 0.37

Coefficients of other control variables

Discharge ports 

Jomi, Tajikistan Dropped Dropped

Abidjan, Cote d’Ivoire 6.635** -0.685

Adale, Somalia 80.198*** 90.836***

Aden, Yemen -8.507 -8.015

Alexandria, Egypt -68.645*** -68.837***

Ashdod, Israel 5.573 5.923

Bangkok, Thailand -23.516*** -23.700***

Barranquilla, Columbia 3.177 3.252

Beira, Somalia 22.448*** 22.335***

Benghazi, Libya -46.713*** -45.725***

Berbera, Somalia -15.124** -5.162

Bosasso, Somalia 52.818*** 64.966***

Calcutta, India 13.542* 14.604*

Cap-Haitien, Haiti -18.186** -20.480**

Chittagong, Bangladesh 2.585 5.188

Colombo, Sri Lanka -1.512 0.127

Cotonou, Benin -11.132** -13.402**

Dakar, Senegal -30.519*** -31.210***

Dar Es Salaam, Tanzania 10.183** 9.598*

Djibouti, Djibouti -7.882 -8.732

Douala, Cameroon 5.39 3.714

Durban, South Africa 7.453 4.476

Fort Dauphin, Madagascar 9.796 16.189*

General Santos City, Philippines 49.923*** 50.207***

Gonaives, Haiti -1.479 0.499

Guayaquil, Ecuador -20.077** -19.961**

Hodeiyah, Yemen 19.804*** 18.562***

Jacmel, Haiti -53.479*** -51.501***

Karachi, Pakistan -4.945 -3.551

Laem Chabang, Thailand -37.967*** -40.693***

Lome, Togo -22.372*** -24.901***

Manila, Philippines 5.152 7.905

Matadi, Democratic Republic of Congo 15.063** 14.688*
Appendix II: Delivery Time Frames Regression 

Analysis

Page 37 GAO-14-277 Prepositioning of Emergency Food Aid

 Prepositioning regression 

Domestic and overseas

prepositioning regression

Misurata, Libya -12.642 -10.867

Mogadishu, Somalia 98.367*** 110.285***

Mombasa, Kenya 14.631*** 14.954***

Monrovia, Liberia -31.973*** -38.442***

Nouakchott, Mauritania -32.020*** -30.749***

Oran, Algeria 17.651*** 15.388***

Polloc, Philippines 36.141*** 39.586***

Port-Au-Prince, Haiti -26.111*** -34.224***

Port Sudan, Sudan 16.398*** 18.560***

Port Qasim, Pakistan -22.322*** -21.066***

Santo Tomas, Guatemala -30.379** -31.267***

Tema, Ghana -49.695*** -43.731***

Toliara, Madagascar 17.957*** 23.456***

Trincomalee, Sri Lanka -23.951*** -22.696***

Year of order 

Ordered 2008 56.024*** 52.333***

Ordered 2009 21.312*** 17.922**

Ordered 2010 10.169** 7.774

Ordered 2011 11.609*** 9.876***

Ordered 2012 Dropped Dropped

Month of order 

Ordered January Dropped Dropped

Ordered February 7.361 8.926

Ordered March 25.336*** 26.426***

Ordered April 20.218*** 20.951***

Ordered May 11.224* 13.165**

Ordered June 4.923 5.932

Ordered July 18.563** 20.328***

Ordered August 7.747 9.484

Ordered September -6.654 -8.178

Ordered October 12.974*** 14.667***

Ordered November 13.676 14.626

Ordered December 17.383 18.921

Commodity 

Beans Dropped Dropped

Bulgur 17.683* 21.491**
Appendix II: Delivery Time Frames Regression 

Analysis

Page 38 GAO-14-277 Prepositioning of Emergency Food Aid

 Prepositioning regression 

Domestic and overseas

prepositioning regression

Corn soya blend -10.246 -5.679

Lentils -16.341 -16.984

Maize 15.303** 15.467**

Peas -5.21 -4.053

Rice 3.044 3.976

Sorghum -32.612*** -31.433***

Vegetable oil -19.131*** -16.100***

Wheat -16.190* -15.305*

Wheat flour 24.436*** 25.118***

Wheat soya blend 31.108*** 29.090***

Bulk/packaged commodity 4.114 5.982

Source: GAO analysis of WFP data.

Notes:

Data provided by WFP do not distinguish diversions from other types of shipments.

In each category of control variables, one variable is dropped from the regression to serve as the 

comparison group for the other dummy variables in that category.

* = significant at the 10 percent significance level. 

** = significant at the 5 percent significance level. 

*** = significant at the 1 percent significance level.

Table 10: Estimated Days Saved by USAID’s Prepositioning Emergency Food Aid for Nine Cooperating Sponsors, Relative to 

Standard Shipping, Fiscal Years 2007-2012

 Prepositioning regression 

Domestic and overseas 

prepositioning regression

Coefficients and standard errors for prepositioning 

Prepositioning (domestic or overseas) -66.788*** 

Standard error <4.445> 

Domestic prepositioning -61.912***

Standard error <6.301> 

Overseas prepositioning -72.910***

Standard error <4.726> 

Sample size 1010 1010

Adjusted R squared 0.64 0.64

Coefficients of other control variables

Freight forwarder 

Freight Forwarder 1 Dropped Dropped
Appendix II: Delivery Time Frames Regression 

Analysis

Page 39 GAO-14-277 Prepositioning of Emergency Food Aid

 Prepositioning regression 

Domestic and overseas 

prepositioning regression

Freight Forwarder 2 -119.973*** -123.149***

Freight Forwarder 3 36.516*** 35.071***

Cooperating sponsor 

CARE Dropped Dropped

Catholic Relief Services 181.208*** 182.788***

Government of Pakistan -17.235 -17.975

Norwegian People’s Aid 46.588*** 42.273***

Relief Society of Tigray 63.317*** 62.116***

SHARE Guatemala 76.939*** 76.419***

Save the Children -11.008** -10.411**

Save the Children - United Kingdom 35.602** 34.279**

Discharge ports 

Jomi, Tajikistan Dropped Dropped

Addis Ababa, Ethiopia 47.108*** 47.365***

Bujumbura, Burundi 153.000*** 153.000***

Chittagong, Bangladesh 23.739** 23.370**

Corinto, Nicaragua -51.946*** -51.695***

Dessie, Ethiopia 44.067*** 45.072***

Dire Dawa, Ethiopia 23.175*** 24.418***

Djibouti, Djibouti 16.804*** 17.575***

Dushanbe, Tajikistan -41.595** -42.900**

Garm, Tajikistan -9.79 -11.37

Gonaives, Haiti -92.977*** -93.953***

Harare, Zimbabwe 10.627 18.830*

Kombolcha, Ethiopia 26.080*** 27.132***

Kur-Tiube, Tajikistan 5.991 4.505

Les Cayes, Haiti -21.876*** -23.158***

Mekele, Ethiopia 28.829*** 30.218***

Mombasa, Kenya 12.519** 13.609***

Multiple destinations, Niger 51.022*** 50.727***

Multiple destinations, Sudan 120.180*** 118.659***

Multiple destinations, Zimbabwe 64.023*** 65.813***

Nairobi, Kenya 43.667*** 43.667***

Nazareth, Ethiopia 18.562** 19.793***

Port-Au-Prince, Haiti -33.714*** -34.662***

Port Sudan, Sudan 13.667*** 13.667***
Appendix II: Delivery Time Frames Regression 

Analysis

Page 40 GAO-14-277 Prepositioning of Emergency Food Aid

 Prepositioning regression 

Domestic and overseas 

prepositioning regression

Santo Tomas, Guatemala -54.899*** -55.877***

Segou, Mali 17.957** 14.550*

Shodecosa, Haiti -53.898*** -54.770***

Woldiya, Ethiopia 61.329*** 63.357***

Year of order 

Ordered 2006 12.691* 16.002***

Ordered 2007 41.919*** 42.865***

Ordered 2008 32.387*** 34.037***

Ordered 2009 40.613*** 42.361***

Ordered 2010 25.187*** 26.850***

Ordered 2011 32.450*** 34.547***

Ordered 2012 Dropped Dropped

Month of order 

Ordered January Dropped Dropped

Ordered February -19.309** -20.253**

Ordered March 7.177 7.217

Ordered April -19.993*** -20.565***

Ordered May -14.418** -15.988**

Ordered June -10.922 -12.936

Ordered July -3.362 -5.401

Ordered August -4.318 -5.577

Ordered September 23.483*** 22.069**

Ordered October 18.902** 17.937**

Ordered November 23.542* 23.791*

Ordered December -0.257 -1.333

Commodity 

Beans Dropped Dropped

Bulgur 2.23 2.624

Corn soya blend 2.288 2.621

Lentils 1.028 1.553

Maize -20.599*** -22.827***

Peas 1.483 1.175

Rice 6.563*** 6.810***

Sorghum -32.716*** -32.758***

Vegetable oil -22.292*** -21.729***

Wheat -43.782*** -44.036***
Appendix II: Delivery Time Frames Regression 

Analysis

Page 41 GAO-14-277 Prepositioning of Emergency Food Aid

 Prepositioning regression 

Domestic and overseas 

prepositioning regression

Wheat flour 11.16 11.567

Bulk/packaged commodity -11.237** -11.298**

Source: GAO analysis of cooperating sponsors’ freight forwarders’ data.

Notes:

In each category of control variables, one variable is dropped from the regression to serve as the 

comparison group for the other dummy variables in that category. Other variables may also be 

dropped due to insufficient number of shipments.

* = significant at the 10 percent significance level. 

** = significant at the 5 percent significance level. 

*** = significant at the 1 percent significance level.

To isolate the effect of diverted shipments on the delivery time frame of 

emergency food aid, we estimated ordinary least squares regression 

models that control for characteristics of diverted shipments, 

prepositioning shipments, and standard shipments. Table 11 shows the 

results of our regression analysis, demonstrating the average number of 

days saved by diversions relative to standard shipping time frames.

Specifically, we estimate Yi = α + β1Diverti + β2DomesticPrepoi + 

β3OverseasPrepoi + δXi + εi for the second column, where Yi is the 

delivery time frame of shipment i; Diverti is a dummy for when shipment i

is diverted; DomesticPrepoi is a dummy for when shipment i is from 

domestic prepositioning; OverseasPrepoi is a dummy for when shipment i

is from overseas prepositioning; and Xi are the control variables listed in 

column 1.12 We clustered the standard errors by the discharge port or 

recipient country. We include the freight forwarder, the cooperating 

sponsor, the discharge port or recipient countries, the year of the 

commodity request, the month of the commodity request, and the 

commodity type. These variables are known to USAID when cooperating 

sponsors submit requests for commodities.13 Controlling for these 

variables allowed us to compare shipments fulfilling requests with the 

 

12These regression results are robust to removing outliers and influential shipments.

Removing the slowest and fastest shipments and influential shipments yields similar 

regression results. 

13Cooperating sponsors’ requests also include the tonnage requested. However, USAID 

decides how much tonnage to include in each shipment when it decides whether to source 

the shipment from the standard shipping process or prepositioned warehouses. USAID 

may source part of the request from food aid diversions and the rest from the standard 

shipping process. 

Food Aid Diversions
Appendix II: Delivery Time Frames Regression 

Analysis

Page 42 GAO-14-277 Prepositioning of Emergency Food Aid

same characteristics. We did not control for the shipment’s tonnage, the 

port of loading, and other variables that USAID determines when deciding 

whether to fulfill a sponsor’s request with commodities sourced from the 

standard shipping process or with food aid diversions.14

Table 11: Estimated Days Saved by USAID’s Diversion of Prepositioning Emergency 

Food Aid Shipments, Relative to Standard Shipping, Fiscal Years 2007–2012

 

Diversion, domestic, 

and overseas 

prepositioning 

regression

Coefficients and standard errors for prepositioning and diversion 

Diversion -63.885***

Standard error <11.023> 

Domestic prepositioning -68.780***

Standard error <7.073> 

Overseas prepositioning -72.867***

Standard error <5.883> 

Sample size 1648

Adjusted R squared 0.71

Coefficients of other control variables

Freight forwarder 

Freight Forwarder 1 Dropped

Freight Forwarder 2 10.446

Freight Forwarder 3 16.281

Cooperating sponsor 

ACDI/VOCA Dropped

Adventist Development and Relief Agency -30.571***

CARE -3.332

Counterpart International -6.686

Catholic Relief Services 24.096

Feed the Hungry 40.335***

Government of Pakistan -19.811*

Norwegian People’s Aid 30.096

 

14We estimated models controlling for the shipment’s tonnage and the flag of the ocean 

vessel which yielded similar regression results.
Appendix II: Delivery Time Frames Regression 

Analysis

Page 43 GAO-14-277 Prepositioning of Emergency Food Aid

 

Diversion, domestic, 

and overseas 

prepositioning 

regression

Relief Society of Tigray 35.514**

SHARE Guatemala 48.243***

Save the Children -17.524**

Save the Children - United Kingdom 10.192

UNICEF -25.773

WFP 9.039

World Vision 24.761**

Discharge ports 

Addis Ababa, Ethiopia Dropped

Aqaba, Jordan -9.877

Bangkok, Thailand -31.090***

Beira, Mozambique -23.063***

Bujumbura, Burundi 110.909***

Calcutta, India -10.841

Chittagong, Bangladesh -16.858**

Colombo, Sri Lanka -48.876***

Corinto, Nicaragua -73.778***

Cotonou, Benin -37.861***

Dakar, Senegal -94.186***

Dar Es Salaam, Tanzania -30.353***

Dessie, Ethiopia -0.695

Dire Dawa, Ethiopia -22.083***

Djibouti, Djibouti -53.199***

Douala, Cameroon -42.541***

Doutchi, Niger 19.166**

Durban, South Africa -31.926***

Dushanbe, Tajikistan -58.383***

Garm, Tajikistan -25.068*

Gonaives, Haiti -125.847***

Harare, Zimbabwe -49.705***

Kampala, Uganda -42.091***

Karachi, Pakistan -46.621***

Kombolcha, Ethiopia -19.891***

Kur-Tiube, Tajikistan -11.474

Laffiteau, Haiti -125.802***
Appendix II: Delivery Time Frames Regression 

Analysis

Page 44 GAO-14-277 Prepositioning of Emergency Food Aid

 

Diversion, domestic, 

and overseas 

prepositioning 

regression

Las Palmas, Canary Islands -44.887***

Les Cayes, Haiti -55.181***

Lome, Togo -53.503***

Mekele, Ethiopia -16.300***

Mombasa, Kenya -32.409***

Monrovia, Liberia -26.006***

Multiple destinations, Niger 9.328

Multiple destinations, Sudan 85.267***

Multiple destinations, Zimbabwe 18.261***

Nairobi, Kenya 1.575

Nampo, North Korea -45.988***

Nazareth, Ethiopia -24.744***

Nouakchott, Mauritania -95.186***

Port-Au-Prince, Haiti -81.237***

Port Sudan, Sudan -28.425***

Port Qasim, Pakistan -57.161***

Santo Tomas, Guatemala -86.743***

Segou, Mali -29.550***

Shodecosa, Haiti -75.984***

Tanout, Niger -4.354

Tema, Ghana -39.412***

Woldiya, Ethiopia 12.5

Yemen -45.658***

Year of order 

Ordered 2006 1.175

Ordered 2007 27.133***

Ordered 2008 13.920*

Ordered 2009 20.852***

Ordered 2010 12.236*

Ordered 2011 14.157**

Ordered 2012 Dropped

Month of order 

Ordered January Dropped

Ordered February -11.198**

Ordered March -2.652
Appendix II: Delivery Time Frames Regression 

Analysis

Page 45 GAO-14-277 Prepositioning of Emergency Food Aid

 

Diversion, domestic, 

and overseas 

prepositioning 

regression

Ordered April -14.918**

Ordered May -9.713**

Ordered June -9.365

Ordered July -5.312

Ordered August -2.149

Ordered September 30.048***

Ordered October 15.184***

Ordered November 5.523

Ordered December 2.506

Commodity 

Beans 6.556

Bulgur 5.425

Corn soya blend 5.597

Lentils -14.277

Maize 6.924

Peas 10.011

Ready-to-use therapeutic food -25.402**

Rice -7.06

Sorghum -37.349***

Vegetable oil 8.157

Wheat -9.729**

Wheat flour Dropped

Bulk/packaged commodity 10.446

Source: GAO analysis of cooperating sponsors’ freight forwarders’ data.

Notes:

In each category of control variables, one variable is dropped from the regression to serve as the 

comparison group for the other dummy variables in that category. Other variables may also be 

dropped due to insufficient number of shipments.

* = significant at the 10 percent significance level.

** = significant at the 5 percent significance level.

*** = significant the 1 percent level. 
Appendix III: Examples of Additional Ocean 

Shipping Costs for Overseas Prepositioning

Page 46 GAO-14-277 Prepositioning of Emergency Food Aid

To derive examples of the additional cost of the second leg of ocean 

shipping for prepositioning, we first estimated the costs of shipping from 

the United States to the prepositioning warehouse in Djibouti and from the 

Djibouti warehouse to three discharge ports—Mombasa, Kenya; Dar es

Salaam, Tanzania; and Beira, Mozambique—in fiscal year 2012. We then 

compared those estimates with the estimated cost of shipping from U.S. 

ports directly to the three ports. (See table 12).1

Table 12: Illustrative Examples of Additional Costs for Ocean Shipping from Djibouti in Fiscal Year 2012, per Metric Ton

Discharge port

Estimated cost of shipping 

from United States to discharge 

port via Djibouti warehousea

Estimated cost of shipping 

directly from United States to 

discharge portb

Estimated additional cost of 

shipping from Djibouti 

warehouse to discharge portc

Mombasa, Kenya $293 $174 $119

Dar es Salaam, Tanzania 322 173 149

Beira, Mozambique 300 172 129

Source: GAO analysis of USAID data.

a

To estimate the cost of shipping from the United States to the discharge ports via Djibouti, we used 

average rates for shipments from U.S. ports to USAID’s prepositioning warehouse in Djibouti and 

actual rates for shipments from the Djibouti warehouse to the discharge ports in fiscal year 2012.

b

To estimate the cost of shipping directly from the United States to the discharge ports, we used 

average rates for such shipments in fiscal year 2012.

c

To estimate the additional cost of shipping from the Djibouti warehouse to the discharge ports, we 

subtracted the estimated cost of shipping directly from the United States to the discharge ports from 

the estimated cost of shipping from the United States to the discharge ports via Djibouti.

 

1

We selected these three routes as illustrative examples to demonstrate how the second 

leg of transportation can represent an additional cost. In some cases, costs associated 

with the second leg of ocean shipping, from a prepositioning warehouse to a discharge 

port, might not be the same as the reconstructed cost differential. 

Appendix III: Examples of Additional Ocean 

Shipping Costs for Overseas Prepositioning
Appendix IV: Analysis of Weighted Annual 

Average Prices for Domestic and Overseas 

Prepositioned Commodities

Page 47 GAO-14-277 Prepositioning of Emergency Food Aid

To identify additional commodity costs associated with USAID’s domestic 

and overseas prepositioning of emergency food aid, we compared the 

weighted average annual prices paid for six key prepositioned 

commodities with the weighted average annual prices paid for each of 

those commodities for standard shipments of emergency food aid in fiscal 

years 2007 through 2012. We found that, relative to standard shipments,

the weighted average annual prices were higher relative to standard 

shipments for domestically prepositioned commodities more often than for 

overseas prepositioned commodities.

As figure 3 shows, for domestically prepositioned commodities, the 

weighted average annual prices were higher relative to standardshipment commodities in 24 instances and lower in 8 instances. For 

overseas prepositioned commodities, the prices relative to standardshipment commodities were higher in 13 instances and lower in 9 

instances. Additionally, the size of the percentage differences between 

prices for prepositioned commodities relative to standard-shipment 

commodities was generally larger for domestic prepositioning than for 

overseas prepositioning. For domestically prepositioned commodities, the 

difference exceeded 15 percent in 7 instances; for overseas 

prepositioned commodities, the difference reached 15 percent in only one 

instance. Weighted annual average prices were consistently higher for 

two domestically prepositioned commodities, corn-soy blend (2007-2011) 

and vegetable oil (2007-2012).

Appendix IV: Analysis of Weighted Annual 

Average Prices for Domestic and Overseas 

Prepositioned Commodities
Appendix IV: Analysis of Weighted Annual 

Average Prices for Domestic and Overseas 

Prepositioned Commodities

Page 48 GAO-14-277 Prepositioning of Emergency Food Aid

Figure 3: Percentage Differences between Weighted Annual Average Prices for USAID’s Domestically and Overseas 

Prepositioned Commodities Relative to Standard-Shipment Commodities, Fiscal Years 2007-2012
Appendix IV: Analysis of Weighted Annual 

Average Prices for Domestic and Overseas 

Prepositioned Commodities

Page 49 GAO-14-277 Prepositioning of Emergency Food Aid

Notes:

The graph shows the percentage differences between the weighted annual average prices per ton for 

six key prepositioned commodities and the weighted annual average prices per ton for the same 

standard-shipment (i.e., nonprepositioned) commodities purchased in the same year. A percentage 

difference higher than 0 indicates a higher weighted average price for the prepositioned commodity 

than for the standard-shipment commodity. A percentage difference lower than 0 indicates a lower 

weighted annual average price for the prepositioned commodity than for the standard-shipment 

commodity.

The listed commodities represented 76 percent of commodities purchased for domestic 

prepositioning in fiscal years 2007 through 2012.

To further examine price differentials between prepositioned and 

standard-shipment commodities, we analyzed the number of purchases 

per year in fiscal years 2007 through 2012. For commodities that the U.S. 

government purchased infrequently, the differences in the average prices 

might be a result of monthly commodity price fluctuations. For example, 

the U.S. government made only one purchase of pinto beans in 2008 and 

two purchases in 2009 for domestic prepositioning. In comparison, there 

were 81 purchases of pinto beans in 2008 and 75 in 2009 for standard 

shipments. Table 13 lists the numbers purchases for domestic 

prepositioning and for standard shipment in fiscal years 2007 to 2012.

Table 13: Numbers of Domestic Prepositioning and Standard Shipment Purchases for Six Key Commodities, Fiscal Years 

2007-2012

Source: GAO analysis of USAID data.

Note: The listed commodities represented 76 percent of commodities purchased for prepositioning in 

fiscal years 2007 through 2012.

2007 2008 2009 2010 2011 2012

Pinto beans (50 kg bag) Domestic prepositioning 9 1 2 24 20 0 

Standard shipment 75 81 75 30 15 37

Corn-soy blend (25 kg bag) Domestic prepositioning 6 14 9 7 11 2 

Standard shipment 117 62 68 62 54 44

Cornmeal (25 kg bag) Domestic prepositioning 20 25 12 0 0 0 

Standard shipment 195 89 100 67 65 57

Vegetable oil (6/4 liter can) Domestic prepositioning 5 10 12 7 5 3 

Standard shipment 159 132 76 65 62 49

Yellow split peas (50 kg bag) Domestic prepositioning 12 7 15 7 8 17

Standard shipment 114 146 135 96 93 127

Sorghum (50 kg bag) Domestic prepositioning 2 4 6 2 3 1 

Standard shipment 6 3 7 5 7 5 
Appendix V: Related GAO Products about

International Food Aid

Page 50 GAO-14-277 Prepositioning of Emergency Food Aid

These products can be downloaded from the links shown or can be found 

on the GAO website at http://www.gao.gov . 

Global Food Security: USAID Is Improving Coordination but Needs to 

Require Systematic Assessments of Country-Level Risks. GAO-13-809. 

Washington, D.C.: September 17, 2013. E-supplement GAO-13-815SP. 

International Food Assistance: U.S. Nonemergency Food Aid Programs 

Have Similar Objectives but Some Planning Helps Limit Overlap. 

GAO-13-141R. Washington, D.C., December 12, 2012.

International Food Assistance: Improved Targeting Would Help Enable 

USAID to Reach Vulnerable Group. GAO-12-862. Washington, D.C.: 

September 24, 2012.

World Food Program: Stronger Controls Needed in High-Risk Areas. 

GAO-12-790. Washington, D.C.: September 13, 2012.

Farm Bill: Issues to Consider for Reauthorization. GAO-12-338SP. 

Washington, D.C.: April 24, 2012.

International Food Assistance: Funding Development Projects through 

the Purchase, Shipment, and Sale of U.S. Commodities Is Inefficient and 

Can Cause Adverse Market Impacts. GAO-11-636. Washington, D.C.: 

June 23, 2011.

International Food Assistance: Better Nutrition and Quality Control Can 

Further Improve U.S. Food Aid. GAO-11-491. Washington, D.C.: May 12, 

2011.

International School Feeding: USDA’s Oversight of the McGovern-Dole 

Food for Education Program Needs Improvement. GAO-11-544. 

Washington, D.C.: May 19, 2011.

International Food Assistance: A U.S. Governmentwide Strategy Could 

Accelerate Progress toward Global Food Security. GAO-10-212T. 

Washington, D.C.: October 29, 2009.

International Food Assistance: Key Issues for Congressional Oversight. 

GAO-09-977SP. Washington, D.C.: September 30, 2009.

Appendix V: Related GAO Products about 

International Food Aid
Appendix V: Related GAO Products about 

International Food Aid

Page 51 GAO-14-277 Prepositioning of Emergency Food Aid

International Food Assistance: Local and Regional Procurement Can 

Enhance the Efficiency of U.S. Food Aid, but Challenges May Constrain 

Its Implementation. GAO-09-570. Washington, D.C.: May 29, 2009.

International Food Security: Insufficient Efforts by Host Governments and 

Donors Threaten Progress to Halve Hunger in Sub-Saharan Africa by 

2015. GAO-08-680. Washington, D.C.: May 29, 2008.

Foreign Assistance: Various Challenges Impede the Efficiency and 

Effectiveness of U.S. Food Aid. GAO-07-560. Washington, D.C.: April 13, 

2007.
Appendix VI: Comments from the U.S. Agency 

for International Development

Page 52 GAO-14-277 Prepositioning of Emergency Food Aid

Appendix VI: Comments from the U.S. 

Agency for International Development

GAO received USAID 

letter on February 25, 

2014.
Appendix VI: Comments from the U.S. Agency 

for International Development

Page 53 GAO-14-277 Prepositioning of Emergency Food Aid
Appendix VII: GAO Contact and Staff 

Acknowledgments

Page 54 GAO-14-277 Prepositioning of Emergency Food Aid

Thomas Melito, (202) 512-9601 or melitot@gao.gov

In addition to the contact named above, Valérie Nowak (Assistant 

Director), Farahnaaz Khakoo-Mausel, Teresa Abruzzo Heger, Ming Chen, 

Fang He, Rhonda Horried, Carol Bray, Martin De Alteriis, Justin Fisher, 

Mark Dowling, Reid Lowe, Todd Anderson, Sushmita SriKanth, John 

O’Trakoun, Barbara Shields, Patrick Hickey, Gergana Danailova-Trainor, 

Gezahegne Bekele, and Etana Finkler made key contributions to this 

report.

Appendix VII: GAO Contact and Staff 

Acknowledgments

GAO Contact

Staff 

Acknowledgments

(320991)
The Government Accountability Office, the audit, evaluation, and 

investigative arm of Congress, exists to support Congress in meeting its 

constitutional responsibilities and to help improve the performance and 

accountability of the federal government for the American people. GAO 

examines the use of public funds; evaluates federal programs and 

policies; and provides analyses, recommendations, and other assistance 

to help Congress make informed oversight, policy, and funding decisions. 

GAO’s commitment to good government is reflected in its core values of 

accountability, integrity, and reliability.

The fastest and easiest way to obtain copies of GAO documents at no 

cost is through GAO’s website (http://www.gao.gov). Each weekday 

afternoon, GAO posts on its website newly released reports, testimony, 

and correspondence. To have GAO e-mail you a list of newly posted 

products, go to http://www.gao.gov and select “E-mail Updates.”

The price of each GAO publication reflects GAO’s actual cost of 

production and distribution and depends on the number of pages in the 

publication and whether the publication is printed in color or black and 

white. Pricing and ordering information is posted on GAO’s website, 

http://www.gao.gov/ordering.htm. 

Place orders by calling (202) 512-6000, toll free (866) 801-7077, or 

TDD (202) 512-2537. 

Orders may be paid for using American Express, Discover Card, 

MasterCard, Visa, check, or money order. Call for additional information.

Connect with GAO on Facebook, Flickr, Twitter, and YouTube. 

Subscribe to our RSS Feeds or E-mail Updates. Listen to our Podcasts. 

Visit GAO on the web at www.gao.gov. 

Contact:

Website: http://www.gao.gov/fraudnet/fraudnet.htm

E-mail: fraudnet@gao.gov

Automated answering system: (800) 424-5454 or (202) 512-7470

Katherine Siggerud, Managing Director, siggerudk@gao.gov, (202) 512-

4400, U.S. Government Accountability Office, 441 G Street NW, Room 

7125, Washington, DC 20548

Chuck Young, Managing Director, youngc1@gao.gov, (202) 512-4800

U.S. Government Accountability Office, 441 G Street NW, Room 7149 

Washington, DC 20548

GAO’s Mission

Obtaining Copies of 

GAO Reports and 

Testimony

Order by Phone

Connect with GAO

To Report Fraud, 

Waste, and Abuse in 

Federal Programs

Congressional 

Relations

Public Affairs

Please Print on Recycled Paper.